WO2018196815A1 - Method and apparatus for obtaining vehicle loss assessment image, server and terminal device - Google Patents

Method and apparatus for obtaining vehicle loss assessment image, server and terminal device Download PDF

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Publication number
WO2018196815A1
WO2018196815A1 PCT/CN2018/084635 CN2018084635W WO2018196815A1 WO 2018196815 A1 WO2018196815 A1 WO 2018196815A1 CN 2018084635 W CN2018084635 W CN 2018084635W WO 2018196815 A1 WO2018196815 A1 WO 2018196815A1
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WO
WIPO (PCT)
Prior art keywords
image
damaged
vehicle
video
damaged part
Prior art date
Application number
PCT/CN2018/084635
Other languages
French (fr)
Chinese (zh)
Inventor
章海涛
侯金龙
郭昕
程远
王剑
徐娟
周凡
张侃
Original Assignee
阿里巴巴集团控股有限公司
章海涛
侯金龙
郭昕
程远
王剑
徐娟
周凡
张侃
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Publication date
Application filed by 阿里巴巴集团控股有限公司, 章海涛, 侯金龙, 郭昕, 程远, 王剑, 徐娟, 周凡, 张侃 filed Critical 阿里巴巴集团控股有限公司
Publication of WO2018196815A1 publication Critical patent/WO2018196815A1/en
Priority to US16/662,837 priority Critical patent/US20200058075A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40—Business processes related to the transportation industry
    • G—PHYSICS
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Definitions

  • the present application belongs to the technical field of computer image data processing, and in particular, to a method, device, server and terminal device for acquiring a vehicle damage image.
  • the insurance company After a vehicle traffic accident occurs, the insurance company needs a number of fixed-loss images to make a damage loss to the risk-taking vehicle, and to archive the data for the risk.
  • the image of the vehicle's fixed damage is usually obtained by the operator on the scene, and then the vehicle is subjected to the fixed damage processing according to the photograph taken on the spot.
  • the image requirements for vehicle damage need to be able to clearly reflect the specific parts of the vehicle damaged, the damaged parts, the type of damage, the degree of damage, etc. This usually requires the photographer to have knowledge of the damage of the professional vehicle in order to take photos and obtain the corresponding damage. Processing the required images, which obviously requires a relatively large manual cost of training and damage processing. Especially in the case of some vehicles that need to evacuate or move the vehicle as soon as possible after a traffic accident, it takes a long time for the insurance company operator to rush to the scene of the accident.
  • the fixed loss image obtained by the owner of the vehicle often does not meet the requirements of the fixed loss image processing due to the non-professional line.
  • the images obtained by the operator on the scene often need to be exported from the shooting device again, and the manual screening is performed to determine the required damage image. This also requires a large manpower and time, thereby reducing the damage required for the final loss processing. Image acquisition efficiency.
  • the existing insurance company operators or vehicle owners take pictures on the spot to obtain the loss image.
  • the professional vehicle damage knowledge is required, the manpower and time cost are large, and the efficiency of obtaining the fixed loss image that meets the requirements of the fixed loss processing is still efficient. Lower.
  • the purpose of the present application is to provide a method, a device, a server and a terminal device for acquiring a vehicle damage image, which can automatically and quickly generate high quality in accordance with the requirements of the fixed loss processing process by the photographer capturing the damaged part of the damaged vehicle.
  • the fixed loss image satisfies the requirements of the fixed loss processing, improves the acquisition efficiency of the fixed loss image, and is convenient for the operator to work.
  • a method, device, server and terminal device for acquiring a vehicle damage image provided by the present application are implemented as follows:
  • a method for acquiring a vehicle damage image comprising:
  • the client acquires the captured video data, and sends the captured video data to the server;
  • a fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  • a method for acquiring a vehicle damage image comprising:
  • a fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  • a method for acquiring a vehicle damage image comprising:
  • a method for acquiring a vehicle damage image comprising:
  • a fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  • a vehicle fixed-loss image acquiring device comprising:
  • a data receiving module configured to receive captured video data of the damaged vehicle and information of the damaged part uploaded by the terminal device, where the damaged part includes a damaged part designated to the damaged vehicle;
  • a classification module configured to extract a video image in the captured video data, classify the video image based on the information of the damaged portion, and determine a candidate image classification set of the specified damaged portion
  • a screening module configured to select a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition.
  • a vehicle fixed-loss image acquiring device comprising:
  • a shooting module for performing video shooting on a damaged vehicle to acquire captured video data
  • An interaction module configured to receive information about the damaged part specified by the damaged vehicle
  • a communication module configured to send the captured video data and the information of the damaged part to a processing terminal
  • a tracking module configured to receive a location area returned by the processing terminal and track the damaged part in real time, and display the tracked location area in real time during video shooting.
  • a vehicle fixed loss image acquisition device includes a processor and a memory for storing processor executable instructions, the processor implementing the instructions to:
  • a fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  • a computer readable storage medium having stored thereon computer instructions that, when executed, implement the following steps:
  • a fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  • a computer readable storage medium having stored thereon computer instructions that, when executed, implement the following steps:
  • a server comprising a processor and a memory for storing processor-executable instructions, the processor implementing the instructions to:
  • a terminal device includes a processor and a memory for storing processor-executable instructions, the processor implementing the instructions to:
  • a fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  • the present invention provides a method, device, server and terminal device for acquiring vehicle damage images, and proposes a video-based automatic generation scheme for vehicle damage images.
  • the photographer can video capture the damaged vehicle through the terminal device and specify the damaged part of the damaged vehicle.
  • the captured video data can be transmitted to the server of the system, and the server analyzes the video data to obtain different types of candidate images required for the loss, and then can generate a lossy image of the damaged vehicle from the candidate image.
  • a high-quality fixed-loss image that meets the requirements of the fixed-loss processing can be automatically and quickly generated, meets the requirements of the fixed-loss processing, improves the acquisition efficiency of the fixed-loss image, and reduces the damage image of the insurance company operator. Get and process costs.
  • FIG. 1 is a schematic flow chart of an embodiment of a method for acquiring a vehicle damage image according to the present application
  • FIG. 2 is a schematic diagram of a scene of specifying a damaged part in one embodiment of the method according to the present application;
  • FIG. 3 is a schematic diagram of a scene in which a damaged portion is specified in another embodiment of the method of the present application;
  • FIG. 4 is a schematic diagram of determining a close-up image based on a damaged portion in an embodiment of the present application
  • FIG. 5 is a schematic diagram of a processing scenario of a method for acquiring a vehicle damage image according to the method of the present application
  • FIG. 6 is a schematic flow chart of another embodiment of the method described in the present application.
  • FIG. 7 is a schematic flow chart of another embodiment of the method described in the present application.
  • FIG. 10 is a block diagram showing a module structure of an embodiment of a vehicle damage image acquisition device provided by the present application.
  • FIG. 11 is a block diagram showing another module structure of an apparatus for acquiring a vehicle damage image provided by the present application.
  • FIG. 12 is a schematic structural diagram of an embodiment of a terminal device provided by the present application.
  • FIG. 1 is a schematic flow chart of an embodiment of a method for acquiring a vehicle damage image according to the present application.
  • the present application provides method operation steps or device structures as shown in the following embodiments or figures, there may be more or partial merged fewer operational steps in the method or device based on conventional or no inventive labor. Or module unit.
  • the execution order of the steps or the module structure of the device is not limited to the execution order or the module structure shown in the embodiment of the present application or the drawings.
  • the device, server or terminal product of the method or module structure When the device, server or terminal product of the method or module structure is applied, it may be executed sequentially or in parallel according to the method or module structure shown in the embodiment or the drawing (for example, parallel processor or multi-thread processing). Environment, even including distributed processing, server cluster implementation environment).
  • the following embodiment describes a scenario in which a specific photographer performs video capture by a mobile terminal and the server processes the captured video data to obtain a lossy image.
  • the photographer can be an insurance company operator, and the photographer holds a mobile terminal to perform video shooting on the damaged vehicle.
  • the mobile terminal may include a mobile phone, a tablet, or other general purpose or special purpose device having a video capture function and a data communication function.
  • the mobile terminal and the server may be deployed with corresponding application modules (such as a certain vehicle loss application APP installed by the mobile terminal to implement corresponding data processing.
  • application modules such as a certain vehicle loss application APP installed by the mobile terminal to implement corresponding data processing.
  • the essence of the solution is applied to other implementation scenarios for acquiring a fixed-loss image of a vehicle.
  • the photographer may also process the video data directly on the mobile terminal side and obtain a fixed-loss image, etc., for the owner of the vehicle or the mobile terminal. .
  • FIG. 1 is an embodiment of a method for acquiring a vehicle damage image provided by the present application, where the method may include:
  • S1 The client acquires the captured video data, and sends the captured video data to the server.
  • the client may include a general-purpose or special-purpose device having a video capturing function and a data communication function, such as a terminal device of a mobile phone, a tablet computer, or the like.
  • the client may also include a fixed computer device (such as a PC end) having a data communication function and a movable video capturing device connected thereto, and the combination is considered as the embodiment.
  • the server may include a processing device that analyzes a frame image in the video data and determines a lossy image.
  • the server may include a logical unit device having image data processing and data communication functions, such as a server of the application scenario of the present embodiment.
  • the server is a second terminal device that performs data communication with the first terminal device when the client is the first terminal device, and thus, for the sake of description,
  • the side on which the captured video data is generated for the vehicle video shooting is referred to as a client, and the side on which the captured video data is processed to generate a fixed-loss image is referred to as a server.
  • This application does not exclude the same terminal device in which the client and the server are physically connected as described in some embodiments.
  • video data captured by the client may be transmitted to the server in real time for the server to process quickly.
  • the video can also be transmitted to the server after the client video capture is completed. If the mobile terminal used by the photographer does not currently have a network connection, video capture can be performed first, and then connected to mobile cellular data or WLAN (Wireless Local Area Networks) or a proprietary network. Of course, even if the client can perform normal data communication with the server, the captured video data can be asynchronously transmitted to the server.
  • WLAN Wireless Local Area Networks
  • the captured video data obtained by the photographer to capture the damaged part of the vehicle may be a video clip or multiple video clips.
  • multi-segment video data generated by shooting at different angles and near and far distances is performed on the same damaged part, or different damaged parts are separately photographed to obtain captured video data of each damaged part.
  • a complete shot can be taken around each damaged part of the damaged vehicle to obtain a relatively long time video clip.
  • S2 The client receives information about the damaged part designated for the damaged vehicle, and sends the information of the damaged part to the server.
  • the damaged portion of the damaged vehicle in the video image may be specified on the client in an interactive manner, and the damaged portion occupies the video image.
  • An area with corresponding area information such as the location and size of the area where the damaged part is located.
  • the client can transmit information about the damaged part specified by the photographer to the server.
  • the photographer uses the mobile terminal to slowly move the captured video vehicle around the damaged vehicle.
  • the area of the damaged part in the video image can be interactively designated on the display screen of the mobile terminal, and the damaged area can be clicked on the display screen by the finger, or an area can be drawn by sliding the finger.
  • FIG. 2 is a schematic diagram of a scene in which a damaged portion is designated in one embodiment of the method according to the present application.
  • the damaged portion sent to the server may be the same shape and size as the photographer draws on the client.
  • the shape format of the damaged portion such as a rectangle, may be set in advance by default. To ensure uniform format of the damaged image, a rectangular area including the smallest area of the damaged portion drawn by the photographer may be generated.
  • FIG. 3 is a schematic diagram of a scene for determining a damaged part in another embodiment of the method according to the present application. When the photographer interacts with the client to specify a damaged part, the figure is drawn by sliding the finger. An irregular trajectory with a 540-pixel abscissa and a 190-pixel astigmatism can generate an area of a 540*190 pixel rectangular damaged portion. The area information of the damaged portion of the rectangle is then sent to the server.
  • the determined location area of the damaged part can be displayed on the client in real time, so that the user can observe and confirm the damaged part.
  • the photographer can specify the damaged part in the corresponding position area of the image through the client, the server can automatically track the specified damaged part, and the size of the corresponding part of the damaged part in the video image and the size of the damaged part as the shooting distance and angle change
  • the location can also change accordingly.
  • the photographer can interactively modify the position and size of the damaged portion.
  • the client determines the location area of the damaged part according to the sliding track of the photographer. If the photographer believes that the default generated location area does not completely cover the damaged part and needs to be adjusted, the position and size of the location area can be adjusted on the client. If the position area is selected by long-pressing the damaged part, move it, adjust the position of the damaged part, or stretch the frame of the damaged part position area to adjust the size. The photographer can generate a new damaged part after the client adjusts the location area of the damaged part, and then sends the new damaged part to the server.
  • the photographer can conveniently and flexibly adjust the position of the damaged part in the video image according to the actual damaged part of the scene, and more accurately locate the damaged part, so that the server can obtain a high-quality fixed-loss image more accurately and reliably.
  • the damaged part designated by the photographer is determined, and the information of the damaged part is sent to the server for processing.
  • the server receives the captured video data and the damaged part information uploaded by the client, extracts a video image in the captured video data, and classifies the video image based on the information of the damaged part, and determines A candidate image classification set of the damaged portion.
  • Vehicle damage often requires different types of image data, such as images of different angles of the vehicle, images showing damaged parts, and close-up details of specific damaged parts.
  • the present application can identify a video image, such as whether it is an image of a damaged vehicle, a vehicle component included in the recognition image, whether one or more vehicle components are included, whether there is damage on the vehicle component, etc. Wait.
  • the fixed loss images required for the vehicle to be damaged may be divided into different categories, and other requirements that do not meet the requirements of the fixed loss image may be separately classified into one category. Specifically, each frame of the captured video may be extracted, and each frame of the image is identified and classified to form a candidate image classification set of the damaged portion.
  • the determined candidate image classification set may include:
  • S301 Display a close-up image set of the damaged part, and display a part image set of the vehicle component to which the damaged part belongs.
  • the close-up image collection includes a close-up image of the damaged portion, and the component image set includes the damaged component of the damaged vehicle, and the damaged component has at least one damaged portion.
  • the photographer can perform shooting from near to far (or from far to near) on the specified damaged portion, which can be completed by the photographer moving or zooming.
  • the server side can classify and identify the frame images in the captured video (which can be processed for each frame image or a frame image of a video segment).
  • the video image of the captured video may be divided into three categories, which are specifically included in the following:
  • the recognition algorithm/classification requirement of the class a image and the like may be determined according to the requirement of the near-field image of the damaged portion in the fixed-loss image.
  • the determination may be determined by the size (area or region span) of the area occupied by the damaged part in the currently located video image. If the damaged portion occupies a large area in the video image (eg, greater than a certain threshold, such as a length or a width greater than a quarter of the video image size), then the video image may be determined to be a type a image.
  • the video image in the close-up image set may be determined by at least one of the following methods:
  • S3011 The area ratio of the damaged area in the video image is greater than the first preset ratio:
  • the ratio of the abscissa span of the damaged part to the length of the associated video image is greater than the second preset ratio, and/or the ratio of the ordinate of the damaged part to the height of the associated video image is greater than the third preset ratio;
  • S3013 Select, from the video image of the same damaged part, the first K video images after the area of the damaged portion is descended, or the video image within the fourth preset ratio after the area is descended, K ⁇ 1.
  • the damaged part In the damaged detail image of type a, the damaged part usually occupies a large area range.
  • the selection of the detailed image of the damaged part can be well controlled, and the type of a that meets the processing requirements is obtained. image.
  • the area of the damaged area in the a type image can be obtained by counting the pixel points contained in the damaged area.
  • the video image is 800*650 pixels
  • two long scratches of the damaged vehicle damage the scratch corresponding to the abscissa span is 600 pixels long
  • the span of each scratch is narrow.
  • the area of the damaged portion is less than one tenth of the video image of the video at this time, since the horizontal span of the damaged portion is 600 pixels, which is three quarters of the length of the entire video image, the video can be used at this time.
  • the image is labeled as a type image, as shown in FIG. 4, which is a schematic diagram of determining a close-up image based on the designated damaged portion in one embodiment of the present application.
  • the area of the damaged portion may be the area of the damaged portion in S3011, or may be the span value of the damaged portion being long or high.
  • a type of image can also be identified in combination with the above various methods, for example, the area of the damaged portion satisfies both a certain proportion of the video image and the fourth pre-region with the largest area in all the same damaged area images. Set within the proportional range.
  • the class a image described in the scene of this embodiment typically contains all or part of the detailed image information of the damaged portion.
  • the first preset ratio, the second preset ratio, the third preset ratio, and the fourth preset ratio described above may be specifically set according to image recognition accuracy or classification accuracy or other processing requirements, for example,
  • the second preset ratio or the third preset ratio may be a quarter.
  • the components included in the video image can be identified by the constructed vehicle component detection model. If the damaged portion is on the detected damaged component, it can be confirmed that the video image belongs to the b-type image.
  • the component detection model described in this embodiment uses a deep neural network to detect the regions of components and components in the image.
  • the component damage recognition model may be constructed based on a Convolutional Neural Network (CNN) and a Region Proposal Network (RPN) in combination with a pooling layer, a fully connected layer, and the like.
  • CNN Convolutional Neural Network
  • RPN Region Proposal Network
  • various models and variants based on convolutional neural networks and regional suggestion networks, such as Faster R-CNN, YOLO, Mask-FCN, etc. can be used.
  • the convolutional neural network (CNN) can use any CNN model, such as ResNet, Inception, VGG, etc. and its variants.
  • the convolutional network (CNN) part of the neural network can use a mature network structure that achieves better effects in object recognition, such as Inception, ResNet, etc., such as a ResNet network, where the input is a picture and the output is a plurality of component areas. And the corresponding component classification and confidence (the confidence here is a parameter indicating the degree of authenticity of the identified vehicle components).
  • Fast R-CNN, YOLO, Mask-FCN, etc. are all deep neural networks including convolutional layers that can be used in this embodiment.
  • the deep neural network used in this embodiment, in conjunction with the region suggestion layer and the CNN layer, can detect the vehicle components in the image to be processed and confirm the component regions of the vehicle component in the image to be processed.
  • the convolutional network (CNN) part of the present application can use a mature network structure in which object recognition achieves good effects, and a ResNet network, which can perform mini-batch gradient descent by using marking data. ) Training is available.
  • the same video image satisfies the judgment logic of the class a and class b images at the same time, it can belong to the class a and class b images at the same time.
  • the server may extract a video image in the captured video data, classify the video image based on location area information of the damaged part in the video image, and determine a candidate image classification set of the specified damaged part. .
  • S4 Select a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition.
  • An image that meets the preset screening condition may be selected from the candidate image classification set according to the category, the sharpness, and the like of the fixed-loss image as the fixed-loss image.
  • the preset screening condition may be a customized setting. For example, in one embodiment, multiple (eg, 5 or 10) sharpness may be selected according to the sharpness of the image in the type a and b images, respectively. And the image with different angles is taken as the fixed damage image of the designated damaged part.
  • the sharpness of the image can be calculated by the image area where the damaged part and the detected vehicle part are located, for example, a space domain based operator (such as a Gabor operator) or a frequency domain based operator (such as a fast Fourier transform) can be used. ) and other methods are obtained.
  • a space domain based operator such as a Gabor operator
  • a frequency domain based operator such as a fast Fourier transform
  • the invention provides a vehicle loss image acquisition method, which provides a video-based vehicle loss generation image automatic generation scheme.
  • the photographer can video capture the damaged vehicle through the terminal device and specify the damaged part of the damaged vehicle.
  • the captured video data can be transmitted to the server side of the system, and the system analyzes the video data on the server side to obtain different types of candidate images required for the loss, and then can generate a lossy image of the damaged vehicle from the candidate image.
  • a high-quality fixed-loss image that meets the requirements of the fixed-loss processing can be automatically and quickly generated, meets the requirements of the fixed-loss processing, improves the acquisition efficiency of the fixed-loss image, and reduces the damage image of the insurance company operator. Get and process costs.
  • the video captured by the client is transmitted to the server, and the server can track the location of the damaged part in the video in real time according to the damaged part.
  • some image algorithms may be used to obtain a correspondence between the adjacent video images of the captured video, such as using optical flow (optical). Flow) algorithm to achieve tracking of damaged parts.
  • the mobile terminal has sensors such as an accelerometer and a gyroscope, the signal data of these sensors can be combined to further determine the direction and angle of the photographer's motion, thereby achieving more accurate tracking of the damaged portion. Therefore, in another embodiment of the method, the method may further include:
  • S200 The server tracks the location area of the damaged part in the captured video data in real time
  • the server determines that the damaged part re-enters the video image after leaving the video image, re-positioning and tracking the location area of the damaged part based on the image feature data of the damaged part.
  • the server can extract image feature data of the damaged area, such as SIFT feature data (Scale-invariant feature transform). If the damaged part is detached from the video image and then re-entered the video image, the system can automatically locate and continue tracking. For example, if the shooting device is powered off and then restarted or the shooting area is displaced to the non-damaged part, it will return to shoot the same damaged part again.
  • SIFT feature data Scale-invariant feature transform
  • the determined location area of the damaged part can be displayed on the client in real time, so that the user can observe and confirm the damaged part.
  • the photographer specifies the damaged part in the corresponding position area of the image through the client, the server can automatically track the specified damaged part, and the size and position of the damaged part in the video image corresponding to the position and position of the damaged part. It can also be changed accordingly.
  • the server side can display the damaged parts tracked by the client in real time, which is convenient for the server operator to observe and use.
  • the server can send the tracked location area of the damaged part to the client during real-time tracking, so that the client can display the damaged part in real time in synchronization with the server, so that the photographer can observe the server. Locate the damaged part of the track. Therefore, in another embodiment of the method, the method may further include:
  • S210 The server sends the tracked location area of the damaged part to the client, so that the client displays the location area of the damaged part in real time.
  • the photographer can interactively modify the position and size of the damaged portion.
  • the client determines the location area of the damaged part according to the sliding track of the photographer. If the photographer believes that the default generated location area does not cover the damaged part and needs to be adjusted, the position and size of the position area can be adjusted. If the position is selected by long-pressing the damaged area, the movement is performed and the adjustment is damaged. The position of the part, or the frame of the area where the damaged part is stretched, can be resized or the like.
  • the photographer can generate a new damaged part after the client adjusts the location area of the damaged part, and then sends the new damaged part to the server.
  • the server can synchronize the new damaged parts modified by the client. The server can identify subsequent video images based on the new damaged portion.
  • the method may further include:
  • S220 Receive a new damaged part sent by the client, where the new damaged part includes the damaged part that is re-determined after the client modifies the location area of the specified damaged part based on the received interactive instruction. ;
  • the classifying the video image based on the information of the damaged portion comprises classifying the video image based on the new damaged portion.
  • the photographer can conveniently and flexibly adjust the position area of the damaged part in the video image according to the actual damaged part of the scene, and more accurately locate the damaged part, so that the server can obtain a high quality fixed loss image.
  • the photographer can continuously shoot from different angles when shooting a close-up of the damaged portion.
  • the server side can obtain the shooting angle of each frame according to the tracking of the damaged part, and then select a set of video images of different angles as the fixed loss image of the damaged part, thereby ensuring that the fixed loss image can accurately reflect the received image.
  • the type and extent of damage Therefore, in another embodiment of the method of the present application, the determining, by the predetermined screening condition, the fixed loss image of the vehicle from the candidate image classification set comprises:
  • S401 Select, from the specified damaged part candidate image classification set, at least one video image as the fixed loss image of the damaged part according to the definition of the video image and the shooting angle of the damaged part.
  • the deformation of the component may be very obvious at some angles relative to other angles, or if the damaged component has reflection or reflection, the reflection or reflection may change with the change of the shooting angle, etc., and the embodiment of the present application is utilized.
  • Selecting images of different angles as fixed loss images can greatly reduce the interference of these factors on the fixed loss.
  • sensors such as accelerometers and gyroscopes on the client, the angles of the shots can also be obtained or assisted by the signals of these sensors.
  • multiple candidate image classification sets may be generated, but only one or more types of candidate image classification sets may be applied when specifically selecting the lossy image, such as the a class and the b class and the above.
  • Class c When selecting the final required fixed loss image, you can specify the candidate image classification set from class a and class b.
  • the type a and b images multiple images can be selected according to the sharpness of the video image (for example, 5 images of the same component are selected, and 10 images of the same damaged portion are selected), and the sharpness is the highest, and the shooting angle is the same. Different images are used as the lossy image.
  • the sharpness of the image can be calculated by calculating the image area of the damaged part and the detected part of the vehicle component, for example, a spatial domain based operator (such as Gabor operator) or a frequency domain based operator (such as fast Fourier) can be used. Transform) and other methods.
  • a spatial domain based operator such as Gabor operator
  • a frequency domain based operator such as fast Fourier
  • Transform and other methods.
  • the photographer can specify a damaged portion each time the video of the mobile terminal is captured, and then transmit it to the server for processing to generate a fixed-loss image of the damaged portion.
  • the user can specify multiple damaged parts at the same time.
  • the server can track the multiple damaged parts at the same time and generate a lossy image of each damaged part.
  • the server acquires the damage image of each damaged part according to the above processing for all the damaged parts designated by the photographer, and then can use all the generated fixed loss images as the fixed damage image of the entire damaged vehicle.
  • FIG. 5 is a schematic diagram of a processing scenario of a method for acquiring a fixed-loss image of a vehicle according to the present application.
  • the tracking processing may be performed at the same time, but the damage is performed.
  • the part C is located on the other side of the damaged vehicle. If the distance between the damaged part A and the damaged part B is far away in the captured video, the damaged part C may not be tracked first, and the damaged part A and the damaged part B are photographed. Then take the damaged part C separately. Therefore, in another embodiment of the method of the present application, if the specified at least two damaged parts are received, it may be determined whether the distance of the at least two damaged parts meets the set neighboring condition;
  • the at least two damaged parts are simultaneously tracked, and corresponding fixed loss images are respectively generated.
  • the proximity condition may be set according to the number of damaged parts in the same video image, the size of the damaged part, the distance between the damaged parts, and the like.
  • the server detects that at least one of the close-up image set and the component image set of the damaged part is empty, or the video image in the close-up image set does not cover all areas corresponding to the damaged part, the video may be generated The prompt message is photographed, and then the video shooting prompt message may be sent to a client corresponding to the captured video data.
  • the server can obtain the b-type fixed-loss image that can determine the vehicle component in which the damaged portion is located, the camera can be fed back to the photographer to shoot adjacent vehicle components including the damaged portion. This ensures that the (b) type of lossy image is obtained. If the server cannot get a type a fixed loss image, or if the type a image does not cover the entire area of the damaged area, it can be fed back to the photographer to be prompted to take a close shot of the damaged part.
  • the server may be prompted Move slowly to ensure the quality of the captured image.
  • the photographer may be prompted Move slowly to ensure the quality of the captured image.
  • feedback to the mobile terminal APP prompts the user to pay attention to the factors such as focus, illumination, etc. when shooting images, such as displaying the prompt message “The speed is too fast, please move slowly to ensure image quality”.
  • the server may retain the video segment that produces the lossy image for subsequent viewing and verification, and the like.
  • the client can upload or copy the fixed loss image to the remote server after the video image is taken.
  • a video-based vehicle loss generation image automatic generation scheme is proposed.
  • the photographer can video capture the damaged vehicle through the terminal device and specify the damaged part of the damaged vehicle.
  • the captured video data can be transmitted to obtain different types of candidate images required for the loss.
  • a fixed loss image of the damaged vehicle can then be generated from the candidate image.
  • a high-quality fixed-loss image that meets the requirements of the fixed-loss processing can be automatically and quickly generated, meets the requirements of the fixed-loss processing, improves the acquisition efficiency of the fixed-loss image, and reduces the damage image of the insurance company operator. Get and process costs.
  • FIG. 6 is a schematic flowchart of another embodiment of the method of the present application. As shown in FIG. 6, the method may include:
  • S11 extracting a video image in the captured video data, classifying the video image based on the information of the damaged part, and determining a candidate image classification set of the designated damaged part;
  • S12 Select a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition.
  • the terminal device may be the client described in the foregoing embodiment, but the application does not exclude other terminal devices, such as a database system, a third-party server, a flash memory, and the like.
  • the server may identify the video image according to the information of the damaged part specified by the photographer on the damaged vehicle. classification.
  • the fixed loss image of the vehicle is then automatically generated by screening.
  • the required lossy image may be correspondingly divided into different categories.
  • the determined candidate image classification set may specifically include:
  • a close-up image collection of the damaged portion is displayed, and a component image set of the vehicle component to which the damaged portion belongs is displayed.
  • the video image in the component image set includes at least one damaged portion, such as a class A close-up view, a b-type component map, a class b, and a b-type image that are not satisfied.
  • the video image in the close-up image set may be determined by at least one of the following:
  • the area ratio of the damaged portion in the area occupied by the video image is greater than the first preset ratio:
  • the ratio of the abscissa span of the damaged portion to the length of the video image to be associated is greater than the second preset ratio, and/or the ratio of the ordinate of the damaged portion to the height of the associated video image is greater than the third predetermined ratio;
  • the first K video images after the area of the damaged portion is descended, or the video image within the fourth preset ratio after the area descending is selected, K ⁇ 1.
  • the recognition algorithm/classification requirement of the class a image and the like can be determined according to the requirements of the near-field image of the damaged portion required for the fixed-loss processing.
  • the determination may be determined by the size (area or region span) of the area occupied by the damaged part in the currently located video image. If the damaged portion occupies a large area in the video image (eg, greater than a certain threshold, such as a length or a width greater than a quarter of the video image size), then the video image may be determined to be a type a image.
  • the current frame image of the other analyzed processing of the damaged component where the damaged portion is located if the current frame image of the other analyzed processing of the damaged component where the damaged portion is located, the area of the damaged portion relative to the other damaged portion is relatively larger. Large (in a certain ratio or TOP range), it can be determined that the current frame image is a type A image.
  • the method further includes:
  • the terminal device may be a client that interacts with the server, such as a mobile phone.
  • the method may further include:
  • the positional area of the damaged part is repositioned and tracked based on the image feature data of the damaged part.
  • the location area of the damaged portion that is repositioned and tracked can be displayed on the server.
  • the method may further include:
  • the determined location area of the damaged part can be displayed on the client in real time, so that the user can observe and confirm the damaged part.
  • the photographer specifies the damaged part in the corresponding position area in the image through the client, and the server can automatically track the designated damaged part, and transmit the tracked position area of the damaged part to the terminal device that captures the video data.
  • the photographer can interactively modify the position and size of the damaged portion.
  • the client determines the location area of the damaged part according to the sliding track of the photographer. If the photographer believes that the default generated location area does not cover the damaged part and needs to be adjusted, the position and size of the position area can be adjusted. If the position is selected by long-pressing the damaged area, the movement is performed and the adjustment is damaged. The position of the part, or the frame of the area where the damaged part is stretched, can be resized or the like.
  • the photographer can generate a new damaged part after the client adjusts the location area of the damaged part, and then sends the new damaged part to the server.
  • the server can synchronize the new damaged parts modified by the client. The server can identify subsequent video images based on the new damaged portion. Therefore, in another embodiment of the method for acquiring a vehicle-damaged image, the method may further include:
  • the classifying the video image based on the information of the damaged portion comprises classifying the video image based on the new damaged portion.
  • the photographer can conveniently and flexibly adjust the position of the damaged part in the video image according to the actual damaged part of the scene, and more accurately locate the damaged part, so that the server can obtain a high quality fixed loss image.
  • the determining a fixed-loss image of the vehicle from the candidate image classification set according to a preset screening condition includes:
  • At least one video image is respectively selected as the fixed loss image of the damaged part according to the sharpness of the video image and the shooting angle of the damaged part.
  • the user can specify multiple damaged parts at the same time.
  • the server can track the multiple damaged parts at the same time and generate a lossy image of each damaged part.
  • the server acquires the damage image of each damaged part according to the above processing for all the damaged parts designated by the photographer, and then can use all the generated fixed loss images as the fixed damage image of the entire damaged vehicle. Therefore, in another embodiment of the method for acquiring a fixed-size image of a vehicle, if at least two damaged parts are received, determining whether the distance of the at least two damaged parts meets the set neighboring condition;
  • the at least two damaged parts are simultaneously tracked, and corresponding fixed loss images are respectively generated.
  • the proximity condition may be set according to the number of damaged parts in the same video image, the size of the damaged part, the distance between the damaged parts, and the like.
  • the present invention further provides an implementation method for acquiring a fixed-loss image of a vehicle that can be used on a client side, based on an embodiment of automatically acquiring a loss-of-loss image by capturing video data from a damaged vehicle, which is described in the foregoing implementation scenario of client-server interaction.
  • FIG. 7 is a schematic flowchart of another embodiment of the method according to the present application. As shown in FIG. 7, the method may include:
  • S20 performing video shooting on the damaged vehicle to obtain captured video data
  • S23 Receive a location area returned by the processing terminal and track the damaged part in real time, and display the tracked location area in real time during video shooting.
  • the processing terminal includes a terminal device that processes the captured video data and automatically generates a lossy image of the damaged vehicle based on information specifying the damaged portion, such as a remote server that can be a fixed-loss image processing.
  • the determined set of candidate image classifications may also include: displaying a close-up image set of the damaged portion, and displaying a component image set of the vehicle component to which the damaged portion belongs.
  • a close-up image set of the damaged portion may also include: displaying a close-up image set of the damaged portion, and displaying a component image set of the vehicle component to which the damaged portion belongs.
  • a component image set of the vehicle component to which the damaged portion belongs Such as the above type a image, b type image, and the like. If the server is unable to obtain a type b fixed-loss image that identifies the vehicle component in which the damaged part is located, the server can feed back to the photographer to send a video capture alert message prompting him to take a number of adjacent vehicle components, including the damaged location, to ensure A type b fixed loss image is obtained.
  • the method may further include:
  • S24 receiving and displaying a video shooting prompt message sent by the processing terminal, where the video shooting prompt message includes at least one of a close-up image set and a component image set of the damaged portion detected by the processing terminal being empty. Or generated when the video image in the close-up image set does not cover the entire area corresponding to the damaged part.
  • the client can display the location area of the damaged part tracked by the server in real time, and can interactively modify the position and size of the location area on the client side. Therefore, in another embodiment of the method, the method may further include:
  • the photographer can perform video shooting on the damaged vehicle through the terminal device and specify the damaged portion of the damaged vehicle.
  • the captured video data can be transmitted to the server of the system, and the server analyzes the video data to obtain different types of candidate images required for the loss, and then can generate a lossy image of the damaged vehicle from the candidate image.
  • the terminal device of the embodiment of the present application video capture of the damaged part on the terminal device and designation of the damaged part, the data information is sent to the server, and the high-quality fixed loss that meets the requirement of the fixed loss processing can be automatically and quickly generated.
  • the image satisfies the requirements of the fixed loss processing, improves the acquisition efficiency of the fixed loss image, and reduces the cost of obtaining and processing the fixed loss image of the insurance company operator.
  • FIG. 8 is a schematic flowchart of another embodiment of the method according to the present application. As shown in FIG. 8, the method includes:
  • S31 Receive information about the damaged part specified by the damaged vehicle, classify the video image in the captured video data based on the information of the damaged part, and determine a candidate image classification set of the damaged part. ;
  • S32 Select a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition.
  • a specific implementation may be composed of application modules deployed on the client.
  • the terminal device may be a general-purpose or special-purpose device with a video capturing function and an image processing capability, such as a mobile phone, a tablet computer, and the like.
  • the photographer can use the client to video capture the damaged vehicle, and analyze the captured video data to generate a lossy image.
  • a server side may also be included to receive the fixed loss image generated by the client.
  • the fixed loss image that the client can generate is transmitted to the specified server in real time or asynchronously. Therefore, another embodiment of the method may further include:
  • S3202 Asynchronously transfer the fixed loss image to a designated server.
  • the client may upload the generated loss image to the remote server immediately, or may upload the loss image in batches afterwards or Copy to the remote server.
  • the method for automatically generating a fixed-loss image by the client side may further include other implementation manners, such as directly generating a video shooting prompt message, based on the foregoing description of the embodiment of the server that automatically generates a fixed-loss image, a damaged portion location tracking, and the like. Displayed on the shooting terminal, specific division and recognition of the damage image category, classification, damage location and tracking. For details, refer to the description of the related embodiments, and details are not described herein.
  • the present invention provides a method for acquiring a vehicle damage image, which can automatically generate a loss image based on a captured video of a damaged vehicle on the client side.
  • the photographer can video capture the damaged vehicle through the client to generate captured video data.
  • the captured video data is analyzed to obtain candidate images of different categories required for the fixed loss.
  • a lossy image of the damaged vehicle can be generated from the candidate image.
  • video shooting can be directly performed on the client side, and a high-quality fixed-loss image that meets the requirements of the fixed-loss processing can be automatically and quickly generated to meet the requirements of the fixed-loss processing and improve the acquisition efficiency of the fixed-loss image. It also reduces the cost of acquiring and processing the damage image of insurance company operators.
  • the present application further provides a vehicle-based damage image acquisition device.
  • the apparatus may include a system (including a distributed system), software (applications), modules, components, servers, clients, etc., using the methods described herein in conjunction with the necessary means of implementing the hardware.
  • the apparatus in one embodiment provided by the present application is as described in the following embodiments. Since the implementation of the device to solve the problem is similar to the method, the implementation of the specific device of the present application can be referred to the implementation of the foregoing method, and the repeated description is not repeated.
  • the term "unit” or "module” may implement a combination of software and/or hardware of a predetermined function.
  • FIG. 10 is a schematic structural diagram of a module of an embodiment of a vehicle-based image loss acquiring apparatus provided by the present application. As shown in FIG. 10, the apparatus may include:
  • the data receiving module 101 may be configured to receive the captured video data of the damaged vehicle and the information of the damaged part uploaded by the terminal device, where the damaged part includes the damaged part designated for the damaged vehicle;
  • the identification classification module 102 may be configured to extract a video image in the captured video data, classify the video image based on the information of the damaged portion, and determine a candidate image classification set of the designated damaged portion;
  • the screening module 103 is configured to select a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition.
  • FIG. 11 is a schematic structural diagram of a module according to another embodiment of the apparatus of the present application, and specifically includes:
  • the shooting module 201 can be configured to perform video shooting on the damaged vehicle to obtain captured video data.
  • the interaction module 201 can be configured to receive information about the damaged part specified by the damaged vehicle;
  • the communication module 202 is configured to send the captured video data and the information of the damaged part to the processing terminal;
  • the tracking module 203 is configured to receive a location area returned by the processing terminal and track the damaged part in real time, and display the tracked location area.
  • the interaction module 201 and the tracking module 203 may be the same processing device, such as a display unit, and the photographer may specify the damaged portion in the display unit, and may also perform display tracking in the display unit. The location area of the damaged part.
  • the method for acquiring a vehicle damage image provided by the present application can be implemented by a processor executing a corresponding program instruction in a computer.
  • the apparatus may include a processor and a memory for storing processor-executable instructions, the processor executing the instruction Time to achieve:
  • a fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  • the device may be a server, and the server receives the captured video data uploaded by the client and the information of the damaged part, and then performs analysis processing to obtain a fixed loss image of the vehicle.
  • the device may also be a client, and the client performs video processing on the damaged vehicle and directly analyzes and processes the image on the client side to obtain a fixed loss image of the vehicle. Therefore, in another embodiment of the apparatus of the present application, the captured video data of the damaged vehicle may include:
  • the terminal device acquires data information uploaded after the video data is captured
  • the vehicle fixed-loss image acquiring device performs captured video data obtained by video capturing the damaged vehicle.
  • the device acquires the captured video data and directly performs the analysis process to obtain the fixed-loss image
  • the obtained fixed-loss image may also be sent to the server for storage or further loss processing. Therefore, in another embodiment of the apparatus, if the captured video data of the damaged vehicle is obtained by video capture of the vehicle-damaged image acquisition device, the processor further includes when the instruction is executed. :
  • the fixed loss image is asynchronously transmitted to a designated processing terminal.
  • the device or the device automatically generates a description of the embodiment of the fixed-loss image, the damaged portion location tracking, and the like.
  • the device for automatically generating the fixed-loss image by the client side may further include other implementation manners, such as generating a video capture.
  • After the prompt message it is directly displayed on the terminal device, the specific division and identification of the fixed loss image category, the classification method, the location and tracking of the damaged part. For details, refer to the description of the related embodiments, and details are not described herein.
  • the photographer can perform video shooting on the damaged vehicle through the vehicle damage image acquisition device provided by the present application to generate captured video data. Then, the captured video data is analyzed to obtain candidate images of different categories required for the fixed loss. Further, a lossy image of the damaged vehicle can be generated from the candidate image.
  • video shooting can be directly performed on the client side, and a high-quality fixed-loss image that meets the requirements of the fixed-loss processing can be automatically and quickly generated to meet the requirements of the fixed-loss processing and improve the acquisition efficiency of the fixed-loss image. It also reduces the cost of acquiring and processing the damage image of insurance company operators.
  • the method or the device described in the above embodiments of the present application can implement the business logic and record on the storage medium by using a computer program, and the storage medium can be read and executed by the computer to achieve the effect of the solution described in the embodiment of the present application. Accordingly, the present application also provides a computer readable storage medium having stored thereon computer instructions that, when executed, may implement the following steps:
  • a fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  • the present application further provides another computer readable storage medium having stored thereon computer instructions that, when executed, implement the following steps:
  • the computer readable storage medium may include physical means for storing information, typically by digitizing the information and then storing it in a medium that utilizes electrical, magnetic or optical means.
  • the computer readable storage medium of this embodiment may include: means for storing information by means of electrical energy, such as various types of memories, such as RAM, ROM, etc.; means for storing information by magnetic energy means, such as hard disk, floppy disk, magnetic tape, magnetic Core memory, bubble memory, U disk; means for optically storing information such as CD or DVD.
  • electrical energy such as various types of memories, such as RAM, ROM, etc.
  • magnetic energy means such as hard disk, floppy disk, magnetic tape, magnetic Core memory, bubble memory, U disk
  • means for optically storing information such as CD or DVD.
  • quantum memories graphene memories, and the like.
  • the apparatus or method described above or the computer readable storage medium may be used in a server for acquiring a vehicle loss image to automatically acquire a vehicle loss image based on the vehicle image video.
  • the server may be a separate server, a system cluster composed of multiple application servers, or a server in a distributed system.
  • the server may include a processor and a memory for storing processor-executable instructions, when the processor executes the instructions:
  • the apparatus or method or the computer readable storage medium described above may be used in a terminal device for acquiring a vehicle loss image to automatically acquire a vehicle loss image based on a vehicle image video.
  • the terminal device may be implemented in the form of a server, or may be implemented by a client that performs video shooting on the damaged vehicle in the field.
  • 12 is a schematic structural diagram of an embodiment of a terminal device provided by the present application.
  • the device on the terminal may include a processor and a memory for storing executable instructions of the processor, where the processing is performed. When the instruction is executed, it can be implemented:
  • a fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  • the processor may further implement the instruction:
  • the fixed loss image is transmitted asynchronously to the designated server.
  • the photographer can perform video shooting on the damaged vehicle through the terminal device of the vehicle-damaged image provided by the present application to generate captured video data. Then, the captured video data is analyzed to obtain candidate images of different categories required for the fixed loss. Further, a lossy image of the damaged vehicle can be generated from the candidate image.
  • video shooting can be directly performed on the client side, and a high-quality fixed-loss image that meets the requirements of the fixed-loss processing can be automatically and quickly generated to meet the requirements of the fixed-loss processing and improve the acquisition efficiency of the fixed-loss image. It also reduces the cost of acquiring and processing the damage image of insurance company operators.
  • PLD Programmable Logic Device
  • FPGA Field Programmable Gate Array
  • HDL Hardware Description Language
  • the controller can be implemented in any suitable manner, for example, the controller can take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (eg, software or firmware) executable by the (micro)processor.
  • computer readable program code eg, software or firmware
  • examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, The Microchip PIC18F26K20 and the Silicone Labs C8051F320, the memory controller can also be implemented as part of the memory's control logic.
  • the controller can be logically programmed by means of logic gates, switches, ASICs, programmable logic controllers, and embedding.
  • Such a controller can therefore be considered a hardware component, and the means for implementing various functions included therein can also be considered as a structure within the hardware component.
  • a device for implementing various functions can be considered as a software module that can be both a method of implementation and a structure within a hardware component.
  • the system, device, module or unit illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product having a certain function.
  • a typical implementation device is a computer.
  • the computer can be, for example, a personal computer, a laptop computer, a car-mounted human-machine interaction device, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet.
  • each module may be implemented in the same software or software, or the modules that implement the same function may be implemented by a plurality of sub-modules or a combination of sub-units.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • there may be another division manner for example, multiple units or components may be combined or integrated. Go to another system, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.
  • the controller can be logically programmed by means of logic gates, switches, ASICs, programmable logic controllers, and embedding.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.
  • a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
  • processors CPUs
  • input/output interfaces network interfaces
  • memory volatile and non-volatile memory
  • the memory may include non-persistent memory, random access memory (RAM), and/or non-volatile memory in a computer readable medium, such as read only memory (ROM) or flash memory.
  • RAM random access memory
  • ROM read only memory
  • Memory is an example of a computer readable medium.
  • Computer readable media includes both permanent and non-persistent, removable and non-removable media.
  • Information storage can be implemented by any method or technology.
  • the information can be computer readable instructions, data structures, modules of programs, or other data.
  • Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory. (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disk read only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, Magnetic tape cartridges, magnetic tape storage or other magnetic storage devices or any other non-transportable media can be used to store information that can be accessed by a computing device.
  • computer readable media does not include temporary storage of computer readable media, such as modulated data signals and carrier waves.
  • embodiments of the present application can be provided as a method, system, or computer program product.
  • the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment in combination of software and hardware.
  • the application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.
  • the application can be described in the general context of computer-executable instructions executed by a computer, such as a program module.
  • program modules include routines, programs, objects, components, data structures, and the like that perform particular tasks or implement particular abstract data types.
  • the present application can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are connected through a communication network.
  • program modules can be located in both local and remote computer storage media including storage devices.

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Abstract

Disclosed are a method and apparatus for obtaining a vehicle loss assessment image, a server and a terminal device. The method comprises: a client obtains photographed video data and transmits the photographed video data to the server; the client receives the information of a specified damaged part of a damaged vehicle, and transmits the information of the damaged part to the server; the server receives the photographed video data and the information of the damaged part which are uploaded by the client, extracts video images in the photographed video data, classifies the video images according to the information of the damaged part, and determines a candidate image classification set of the damaged part; select a loss assessment image of the vehicle from the candidate image classification set according to a preset screening condition. According to embodiments of the present application, a high-quality loss assessment image meeting the loss assessment processing demands can be automatically and quickly generated, meeting the loss assessment processing demands and improving the obtaining efficiency of a loss assessment image.

Description

车辆定损图像获取方法、装置、服务器和终端设备Vehicle fixed loss image acquisition method, device, server and terminal device 技术领域Technical field
本申请属于计算机图像数据处理技术领域，尤其涉及一种车辆定损图像获取方法、装置、服务器和终端设备。The present application belongs to the technical field of computer image data processing, and in particular, to a method, device, server and terminal device for acquiring a vehicle damage image.
背景技术Background technique
发生车辆交通事故后，保险公司需要若干定损图像来对出险车辆进行定损核损，并进行出险的资料进行存档。After a vehicle traffic accident occurs, the insurance company needs a number of fixed-loss images to make a damage loss to the risk-taking vehicle, and to archive the data for the risk.
目前车辆定损的图像通常是由作业人员现场进行拍照获得，然后根据现场拍照的照片进行车辆定损处理。车辆定损的图像要求需要能够清楚的反应出车辆受损的具体部位、损伤部件、损伤类型、损伤程度等信息，这通常需要拍照人员具有专业车辆定损的相关知识，才能拍照获取符合定损处理要求的图像，这显然需要比较大的人力培训和定损处理的经验成本。尤其是在一些发生车辆交通事故后需要尽快撤离或移动车辆现场的情况下，保险公司作业人员赶到事故现场需要耗费较长的时间。并且，如果车主用户主动或者在保险公司作业人员要求下先行拍照，获取一些原始定损图像，由于非专业行，车主用户拍照获得的定损图像常常不符合定损图像处理要求。另外，作业人员现场拍照获得的图像往往也需要后期再次从拍摄设备导出，进行人工筛选，确定需要的定损图像，这同样需要消耗较大人力和时间，进而降低最终定损处理需要的定损图像的获取效率。At present, the image of the vehicle's fixed damage is usually obtained by the operator on the scene, and then the vehicle is subjected to the fixed damage processing according to the photograph taken on the spot. The image requirements for vehicle damage need to be able to clearly reflect the specific parts of the vehicle damaged, the damaged parts, the type of damage, the degree of damage, etc. This usually requires the photographer to have knowledge of the damage of the professional vehicle in order to take photos and obtain the corresponding damage. Processing the required images, which obviously requires a relatively large manual cost of training and damage processing. Especially in the case of some vehicles that need to evacuate or move the vehicle as soon as possible after a traffic accident, it takes a long time for the insurance company operator to rush to the scene of the accident. Moreover, if the owner of the vehicle takes the initiative to take photos or obtain the original fixed loss image at the request of the insurance company operator, the fixed loss image obtained by the owner of the vehicle often does not meet the requirements of the fixed loss image processing due to the non-professional line. In addition, the images obtained by the operator on the scene often need to be exported from the shooting device again, and the manual screening is performed to determine the required damage image. This also requires a large manpower and time, thereby reducing the damage required for the final loss processing. Image acquisition efficiency.
现有的保险公司作业人员或车主用户现场拍照获取定损图像的方式，需要专业的车辆定损的相关知识，人力和时间成本较大，获取符合定损处理需求的定损图像的方式效率仍然较低。The existing insurance company operators or vehicle owners take pictures on the spot to obtain the loss image. The professional vehicle damage knowledge is required, the manpower and time cost are large, and the efficiency of obtaining the fixed loss image that meets the requirements of the fixed loss processing is still efficient. Lower.
发明内容Summary of the invention
本申请目的在于提供一种车辆定损图像获取方法、装置、服务器和终端设 备，通过拍摄者对受损车辆的受损部位进行视频拍摄，可以自动、快速的生成符合定损处理需求的高质量定损图像，满足定损处理需求，提高定损图像的获取效率，便于作业人员作业。The purpose of the present application is to provide a method, a device, a server and a terminal device for acquiring a vehicle damage image, which can automatically and quickly generate high quality in accordance with the requirements of the fixed loss processing process by the photographer capturing the damaged part of the damaged vehicle. The fixed loss image satisfies the requirements of the fixed loss processing, improves the acquisition efficiency of the fixed loss image, and is convenient for the operator to work.
本申请提供的一种车辆定损图像获取方法、装置、服务器和终端设备是这样实现的：A method, device, server and terminal device for acquiring a vehicle damage image provided by the present application are implemented as follows:
一种车辆定损图像获取方法，包括：A method for acquiring a vehicle damage image, comprising:
客户端获取拍摄视频数据，将所述拍摄视频数据发送至服务器；The client acquires the captured video data, and sends the captured video data to the server;
所述客户端接收对受损车辆指定的受损部位的信息，将所述受损部位的信息发送至所述服务器；Receiving, by the client, information about the damaged part designated for the damaged vehicle, and transmitting the information of the damaged part to the server;
所述服务器接收所述客户端上传的拍摄视频数据和受损部位的信息，提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述受损部位的候选图像分类集合；Receiving, by the server, the captured video data and the damaged part information uploaded by the client, extracting a video image in the captured video data, classifying the video image based on the information of the damaged part, and determining the a candidate image classification set of the damaged part;
按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
一种车辆定损图像获取方法，所述方法包括：A method for acquiring a vehicle damage image, the method comprising:
接收终端设备上传的受损车辆的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；Receiving, by the terminal device, captured video data of the damaged vehicle and information of the damaged portion, the damaged portion including the damaged portion designated for the damaged vehicle;
提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述指定受损部位的候选图像分类集合；Extracting a video image in the captured video data, classifying the video image based on information of the damaged portion, and determining a candidate image classification set of the designated damaged portion;
按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
一种车辆定损图像获取方法，所述方法包括：A method for acquiring a vehicle damage image, the method comprising:
对受损车辆进行视频拍摄，获取拍摄视频数据；Video capture of damaged vehicles to obtain captured video data;
接收对所述受损车辆指定的受损部位的信息；Receiving information on the damaged portion designated for the damaged vehicle;
将所述拍摄视频数据和所述受损部位的信息发送至处理终端；Transmitting the captured video data and the information of the damaged part to a processing terminal;
接收所述处理终端返回的对所述受损部位实时跟踪的位置区域，在视频拍摄过程中实时显示所述跟踪的位置区域。Receiving a location area returned by the processing terminal and tracking the damaged part in real time, and displaying the tracked location area in real time during video shooting.
一种车辆定损图像获取方法，所述方法包括：A method for acquiring a vehicle damage image, the method comprising:
接收受损车辆的拍摄视频数据；Receiving captured video data of the damaged vehicle;
接收对所述受损车辆指定的受损部位的信息，基于所述受损部位的信息对所述拍摄视频数据中的视频图像进行识分类，确定所述受损部位的候选图像分类集合；Receiving information about the damaged part specified by the damaged vehicle, classifying the video image in the captured video data based on the information of the damaged part, and determining a candidate image classification set of the damaged part;
按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
一种车辆定损图像获取装置，所述装置包括：A vehicle fixed-loss image acquiring device, the device comprising:
数据接收模块，用于接收终端设备上传的受损车辆的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；a data receiving module, configured to receive captured video data of the damaged vehicle and information of the damaged part uploaded by the terminal device, where the damaged part includes a damaged part designated to the damaged vehicle;
识别分类模块，用于提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述指定受损部位的候选图像分类集合；a classification module, configured to extract a video image in the captured video data, classify the video image based on the information of the damaged portion, and determine a candidate image classification set of the specified damaged portion;
筛选模块，用于按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。And a screening module, configured to select a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition.
一种车辆定损图像获取装置，所述装置包括：A vehicle fixed-loss image acquiring device, the device comprising:
拍摄模块，用于对受损车辆进行视频拍摄，获取拍摄视频数据；a shooting module for performing video shooting on a damaged vehicle to acquire captured video data;
交互模块，用于接收对所述受损车辆指定的受损部位的信息；An interaction module, configured to receive information about the damaged part specified by the damaged vehicle;
通信模块，用于将所述拍摄视频数据和所述受损部位的信息发送至处理终端；a communication module, configured to send the captured video data and the information of the damaged part to a processing terminal;
跟踪模块，用于接收所述处理终端返回的对所述受损部位实时跟踪的位置区域，在视频拍摄过程中实时显示所述跟踪的位置区域。And a tracking module, configured to receive a location area returned by the processing terminal and track the damaged part in real time, and display the tracked location area in real time during video shooting.
一种车辆定损图像获取装置，包括处理器以及用于存储处理器可执行指令的存储器，所述处理器执行所述指令时实现：A vehicle fixed loss image acquisition device includes a processor and a memory for storing processor executable instructions, the processor implementing the instructions to:
接收受损车辆的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；Receiving captured video data of the damaged vehicle and information of the damaged portion, the damaged portion including the damaged portion designated for the damaged vehicle;
提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述指定受损部位的候选图像分类集合；Extracting a video image in the captured video data, classifying the video image based on information of the damaged portion, and determining a candidate image classification set of the designated damaged portion;
按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
一种计算机可读存储介质，其上存储有计算机指令，所述指令被执行时实现以下步骤：A computer readable storage medium having stored thereon computer instructions that, when executed, implement the following steps:
接收对受损车辆进行视频拍摄的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；Receiving captured video data for video capture of the damaged vehicle and information of the damaged portion, the damaged portion including the damaged portion designated for the damaged vehicle;
基于所述受损部位的信息对所述拍摄视频数据中的视频图像进行识分类，确定所述受损部位的候选图像分类集合；Determining a video image in the captured video data based on the information of the damaged portion, and determining a candidate image classification set of the damaged portion;
按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
一种计算机可读存储介质，其上存储有计算机指令，所述指令被执行时实现以下步骤：A computer readable storage medium having stored thereon computer instructions that, when executed, implement the following steps:
对受损车辆进行视频拍摄，获取拍摄视频数据；Video capture of damaged vehicles to obtain captured video data;
接收对所述受损车辆指定的受损部位的信息；Receiving information on the damaged portion designated for the damaged vehicle;
将所述拍摄视频数据和所述受损部位的信息发送至处理终端；Transmitting the captured video data and the information of the damaged part to a processing terminal;
接收所述处理终端返回的对所述受损部位实时跟踪的位置区域，在视频拍摄过程中实时显示所述跟踪的位置区域。Receiving a location area returned by the processing terminal and tracking the damaged part in real time, and displaying the tracked location area in real time during video shooting.
一种服务器，包括处理器以及用于存储处理器可执行指令的存储器，所述处理器执行所述指令时实现：A server comprising a processor and a memory for storing processor-executable instructions, the processor implementing the instructions to:
接收终端设备上传的受损车辆的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述指定受损部位的候选图像分类集合；按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。Receiving captured video data of the damaged vehicle and information of the damaged part uploaded by the terminal device, the damaged part including the damaged part designated for the damaged vehicle; extracting a video image in the captured video data, based on The information about the damaged portion classifies the video image, determines a candidate image classification set of the designated damaged portion, and selects a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition.
一种终端设备，包括处理器以及用于存储处理器可执行指令的存储器，所述处理器执行所述指令时实现：A terminal device includes a processor and a memory for storing processor-executable instructions, the processor implementing the instructions to:
获取对受损车辆进行视频拍摄的拍摄视频数据；Obtaining captured video data for video shooting of damaged vehicles;
接收对所述受损车辆指定的受损部位的信息；Receiving information on the damaged portion designated for the damaged vehicle;
基于所述受损部位的信息对所述拍摄视频数据中的视频图像进行识分类，确定所述受损部位的候选图像分类集合；Determining a video image in the captured video data based on the information of the damaged portion, and determining a candidate image classification set of the damaged portion;
按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
本申请提供的一种车辆定损图像获取方法、装置、服务器和终端设备，提出了基于视频的车辆定损图像自动生成方案。拍摄者可以通过终端设备对受损车辆进行视频拍摄，并指定受损车辆的受损部位。拍摄的视频数据可以传输到系统的服务器，服务器再对视频数据进行分析，获取定损所需的不同类别的候选图像，然后可以从候选图像中产生受损车辆的定损图像。利用本申请实施方案，可以自动、快速的生成符合定损处理需求的高质量定损图像，满足定损处理需求，提高定损图像的获取效率，同时也减少了保险公司作业人员的定损图像获取和处理成本。The present invention provides a method, device, server and terminal device for acquiring vehicle damage images, and proposes a video-based automatic generation scheme for vehicle damage images. The photographer can video capture the damaged vehicle through the terminal device and specify the damaged part of the damaged vehicle. The captured video data can be transmitted to the server of the system, and the server analyzes the video data to obtain different types of candidate images required for the loss, and then can generate a lossy image of the damaged vehicle from the candidate image. By using the embodiment of the present application, a high-quality fixed-loss image that meets the requirements of the fixed-loss processing can be automatically and quickly generated, meets the requirements of the fixed-loss processing, improves the acquisition efficiency of the fixed-loss image, and reduces the damage image of the insurance company operator. Get and process costs.
附图说明DRAWINGS
为了更清楚地说明本申请实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请中记载的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings to be used in the embodiments or the prior art description will be briefly described below. Obviously, the drawings in the following description are only It is a few embodiments described in the present application, and other drawings can be obtained from those skilled in the art without any inventive labor.
图1是本申请所述一种车辆定损图像获取方法实施例的流程示意图；1 is a schematic flow chart of an embodiment of a method for acquiring a vehicle damage image according to the present application;
图2是本申请所述方法一个实施例中指定受损部位的场景示意图；2 is a schematic diagram of a scene of specifying a damaged part in one embodiment of the method according to the present application;
图3是本申请所述方法另一个实施例中指定受损部位的场景示意图；3 is a schematic diagram of a scene in which a damaged portion is specified in another embodiment of the method of the present application;
图4是本申请一个实施例中基于受损部位确定近景图像的示意图；4 is a schematic diagram of determining a close-up image based on a damaged portion in an embodiment of the present application;
图5是本申请所述方一种车辆定损图像获取方法的处理场景示意图；5 is a schematic diagram of a processing scenario of a method for acquiring a vehicle damage image according to the method of the present application;
图6是本申请所述方法另一个实施例的流程示意图；6 is a schematic flow chart of another embodiment of the method described in the present application;
图7是本申请所述方法另一个实施例的流程示意图；7 is a schematic flow chart of another embodiment of the method described in the present application;
图8是本申请所述方法另一个实施例的流程示意图；8 is a schematic flow chart of another embodiment of the method described in the present application;
图9是本申请所述方法另一个实施例的流程示意图；9 is a schematic flow chart of another embodiment of the method described in the present application;
图10是本申请提供的一种车辆定损图像获取装置实施例的模块结构示意图；10 is a block diagram showing a module structure of an embodiment of a vehicle damage image acquisition device provided by the present application;
图11是本申请提供的另一种车辆定损图像获取装置实施例的模块结构示意图；11 is a block diagram showing another module structure of an apparatus for acquiring a vehicle damage image provided by the present application;
图12是本申请提供的一种终端设备实施例的结构示意图。FIG. 12 is a schematic structural diagram of an embodiment of a terminal device provided by the present application.
具体实施方式detailed description
为了使本技术领域的人员更好地理解本申请中的技术方案，下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都应当属于本申请保护的范围。The technical solutions in the embodiments of the present application are clearly and completely described in the following, in which the technical solutions in the embodiments of the present application are clearly and completely described. The embodiments are only a part of the embodiments of the present application, and not all of them. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present application without departing from the inventive scope shall fall within the scope of the application.
图1是本申请所述一种车辆定损图像获取方法实施例的流程示意图。虽然本申请提供了如下述实施例或附图所示的方法操作步骤或装置结构，但基于常规或者无需创造性的劳动在所述方法或装置中可以包括更多或者部分合并后更少的操作步骤或模块单元。在逻辑性上不存在必要因果关系的步骤或结构中，这些步骤的执行顺序或装置的模块结构不限于本申请实施例或附图所示的执行顺序或模块结构。所述的方法或模块结构的在实际中的装置、服务器或终端产品应用时，可以按照实施例或者附图所示的方法或模块结构进行顺序执行或者并行执行(例如并行处理器或者多线程处理的环境、甚至包括分布式处理、服务器集群的实施环境)。1 is a schematic flow chart of an embodiment of a method for acquiring a vehicle damage image according to the present application. Although the present application provides method operation steps or device structures as shown in the following embodiments or figures, there may be more or partial merged fewer operational steps in the method or device based on conventional or no inventive labor. Or module unit. In the steps or structures in which the necessary causal relationship does not exist logically, the execution order of the steps or the module structure of the device is not limited to the execution order or the module structure shown in the embodiment of the present application or the drawings. When the device, server or terminal product of the method or module structure is applied, it may be executed sequentially or in parallel according to the method or module structure shown in the embodiment or the drawing (for example, parallel processor or multi-thread processing). Environment, even including distributed processing, server cluster implementation environment).
为了清楚起见，下述实施例以具体的一个拍摄者通过移动终端进行视频拍摄、服务器对拍摄视频数据进行处理获取定损图像的实施场景进行说明。拍摄者可以为保险公司作业人员，拍摄者手持移动终端对受损车辆进行视频拍摄。所述的移动终端可以包括手机、平板电脑，或者其他有视频拍摄功能和数据通 信功能的通用或专用设备。所述的移动终端和服务器可以部署有相应的应用模块(如移动终端安装的某个车辆定损APP(application，应用)，以实现相应的数据处理。但是，本领域技术人员能够理解到，可以将本方案的实质精神应用到获取车辆定损图像的其他实施场景中，如拍摄者也可以为车主用户，或者移动终端拍摄后直接在移动终端一侧对视频数据进行处理并获取定损图像等。For the sake of clarity, the following embodiment describes a scenario in which a specific photographer performs video capture by a mobile terminal and the server processes the captured video data to obtain a lossy image. The photographer can be an insurance company operator, and the photographer holds a mobile terminal to perform video shooting on the damaged vehicle. The mobile terminal may include a mobile phone, a tablet, or other general purpose or special purpose device having a video capture function and a data communication function. The mobile terminal and the server may be deployed with corresponding application modules (such as a certain vehicle loss application APP installed by the mobile terminal to implement corresponding data processing. However, those skilled in the art can understand that The essence of the solution is applied to other implementation scenarios for acquiring a fixed-loss image of a vehicle. For example, the photographer may also process the video data directly on the mobile terminal side and obtain a fixed-loss image, etc., for the owner of the vehicle or the mobile terminal. .
具体的一种实施例如图1所示，本申请提供的一种车辆定损图像获取方法的一种实施例中，所述方法可以包括：One embodiment of the present invention, as shown in FIG. 1 , is an embodiment of a method for acquiring a vehicle damage image provided by the present application, where the method may include:
S1：客户端获取拍摄视频数据，将所述拍摄视频数据发送至服务器。S1: The client acquires the captured video data, and sends the captured video data to the server.
所述的客户端可以包括具有视频拍摄功能和数据通信功能的通用或专用设备，如手机、平板电脑等的终端设备。本实施例其他的实施场景中，所述的客户端也可以包括具有数据通信功能的固定计算机设备(如PC端)和与其连接的可移动的视频拍摄设备，两者组合后视为本实施例的一种客户端的终端设备。拍摄者通过客户端拍摄视频数据，所述的拍摄视频数据可以传输到服务器。所述的服务器可以包括对所述视频数据中的帧图像进行分析处理并确定出定损图像的处理设备。所述服务器可以包括具有图像数据处理和数据通信功能的逻辑单元装置，如本实施例应用场景的服务器。从数据交互的角度来看，所述服务器是相对于所述客户端作为第一终端设备时的另一个与第一终端设备进行数据通信的第二终端设备，因此，为以便描述，在此可以将对车辆视频拍摄生成拍摄视频数据的一侧称为客户端，将对所述拍摄视频数据进行处理生成定损图像的一侧称为服务器。本申请不排除在一些实施例中所述的客户端与服务器为物理连接的同一终端设备。The client may include a general-purpose or special-purpose device having a video capturing function and a data communication function, such as a terminal device of a mobile phone, a tablet computer, or the like. In other implementation scenarios of the embodiment, the client may also include a fixed computer device (such as a PC end) having a data communication function and a movable video capturing device connected thereto, and the combination is considered as the embodiment. A client terminal device. The photographer captures video data through the client, and the captured video data can be transmitted to the server. The server may include a processing device that analyzes a frame image in the video data and determines a lossy image. The server may include a logical unit device having image data processing and data communication functions, such as a server of the application scenario of the present embodiment. From the perspective of data interaction, the server is a second terminal device that performs data communication with the first terminal device when the client is the first terminal device, and thus, for the sake of description, The side on which the captured video data is generated for the vehicle video shooting is referred to as a client, and the side on which the captured video data is processed to generate a fixed-loss image is referred to as a server. This application does not exclude the same terminal device in which the client and the server are physically connected as described in some embodiments.
本申请的一些实施方式中，客户端拍摄得到的视频数据可以实时传输到服务器，以便于服务器快速处理。其他的实施方式中，也可以在客户端视频拍摄完成后再传输至服务器。如拍摄者使用的移动终端当前没有网络连接，则可以先进行视频拍摄，等连接上移动蜂窝数据或WLAN(Wireless Local Area Networks，无线局域网)或者专有网络后再进行传输。当然，即使在客户端可 以与服务器进行正常数据通信的情况下，也可以将拍摄视频数据异步传输至服务器。In some implementations of the present application, video data captured by the client may be transmitted to the server in real time for the server to process quickly. In other implementation manners, the video can also be transmitted to the server after the client video capture is completed. If the mobile terminal used by the photographer does not currently have a network connection, video capture can be performed first, and then connected to mobile cellular data or WLAN (Wireless Local Area Networks) or a proprietary network. Of course, even if the client can perform normal data communication with the server, the captured video data can be asynchronously transmitted to the server.
需要说明的是，本实施例中拍摄者对车辆受损部位进行拍摄获取的拍摄视频数据，可以为一个视频片段，也可以为多个视频片段。如对同一个受损部位进行了多次不同角度和远近距离的拍摄生成的多段拍摄视频数据，或者对不同的受损部位分别进行拍摄得到各个受损部位的拍摄视频数据。当然，一些实施场景下，也可以围绕受损车辆的各个受损部位进行一次完整拍摄，得到一个相对时间较长的视频片段。It should be noted that, in this embodiment, the captured video data obtained by the photographer to capture the damaged part of the vehicle may be a video clip or multiple video clips. For example, multi-segment video data generated by shooting at different angles and near and far distances is performed on the same damaged part, or different damaged parts are separately photographed to obtain captured video data of each damaged part. Of course, in some implementation scenarios, a complete shot can be taken around each damaged part of the damaged vehicle to obtain a relatively long time video clip.
S2：所述客户端接收对受损车辆指定的受损部位的信息，将所述受损部位的信息发送至所述服务器。S2: The client receives information about the damaged part designated for the damaged vehicle, and sends the information of the damaged part to the server.
在本实施例实施方式中，拍摄者对受损车辆进行视频拍摄时，可以采用交互方式在所述客户端上指定视频图像中受损车辆的受损部位，该受损部位占据视频图像上的一块区域，并有相应的区域信息，如受损部位所在区域的位置和大小等。客户端可以将拍摄者指定的受损部位的信息传输给服务器。In the embodiment of the present embodiment, when the photographer performs video shooting on the damaged vehicle, the damaged portion of the damaged vehicle in the video image may be specified on the client in an interactive manner, and the damaged portion occupies the video image. An area with corresponding area information, such as the location and size of the area where the damaged part is located. The client can transmit information about the damaged part specified by the photographer to the server.
在本实施例应用场景中，拍摄者使用移动终端围绕受损车辆缓慢移动拍摄视频车辆。在拍到受损部位时，可以在移动终端的显示屏上交互式指定受损部位在视频图像中的区域，具体的可以通过手指在显示屏点击受损部位，或者通过手指滑动画出一片区域，如将受损部位圈住，形成一个手指滑动的圆圈轨迹，如图2所示，图2是本申请所述方法一个实施例中指定受损部位的场景示意图。In the application scenario of the embodiment, the photographer uses the mobile terminal to slowly move the captured video vehicle around the damaged vehicle. When the damaged part is photographed, the area of the damaged part in the video image can be interactively designated on the display screen of the mobile terminal, and the damaged area can be clicked on the display screen by the finger, or an area can be drawn by sliding the finger. For example, if the damaged portion is encircled, a circular trajectory of a finger sliding is formed, as shown in FIG. 2, which is a schematic diagram of a scene in which a damaged portion is designated in one embodiment of the method according to the present application.
一种实施中，所述发送给服务器的受损部位的形状和大小可以与拍摄者在客户端上画出的相同。其他的实施方式中，也可以预先默认设定受损部位的形状格式，如矩形，为保障受损图像的格式统一，则可以生成包含拍摄者画出的受损部位的最小面积的矩形区域。具体的一个示例中如图3所示，图3是本申请所述方法另一个实施例中确定受损部位的场景示意图，当拍摄者与客户端交互指定受损部位时，通过手指滑动画出一个横坐标跨度为540像素、纵坐标跨 度为190像素的不规则轨迹，则可以生成一个540*190像素的矩形受损部位的区域。然后将该矩形受损部位的区域信息发送给服务器。In one implementation, the damaged portion sent to the server may be the same shape and size as the photographer draws on the client. In other embodiments, the shape format of the damaged portion, such as a rectangle, may be set in advance by default. To ensure uniform format of the damaged image, a rectangular area including the smallest area of the damaged portion drawn by the photographer may be generated. FIG. 3 is a schematic diagram of a scene for determining a damaged part in another embodiment of the method according to the present application. When the photographer interacts with the client to specify a damaged part, the figure is drawn by sliding the finger. An irregular trajectory with a 540-pixel abscissa and a 190-pixel astigmatism can generate an area of a 540*190 pixel rectangular damaged portion. The area information of the damaged portion of the rectangle is then sent to the server.
拍摄者在客户端上指定车辆受损部位时，确定出的受损部位的位置区域可以实时显示在客户端上，以便于用户观察和确认受损部位。拍摄者可以通过客户端指定受损部位在图像中对应的位置区域，服务器可以自动跟踪指定受损部位，并且随着拍摄距离和角度变化，该受损部位在视频图像中对应的位置区域大小和位置也可以相应的变化。When the photographer specifies the damaged part of the vehicle on the client, the determined location area of the damaged part can be displayed on the client in real time, so that the user can observe and confirm the damaged part. The photographer can specify the damaged part in the corresponding position area of the image through the client, the server can automatically track the specified damaged part, and the size of the corresponding part of the damaged part in the video image and the size of the damaged part as the shooting distance and angle change The location can also change accordingly.
另一种实施方式中，拍摄者可以交互式修改受损部位的位置和大小。例如客户端根据拍摄者的滑动轨迹确定受损部位的位置区域。若拍摄者认为默认生成的位置区域未能全部覆盖受损部位，需要调整，则可以在客户端上调整该位置区域的位置和大小。如长按受损部位选择该位置区域后，进行移动，调整受损部位的位置，或者拉伸受损部位位置区域的边框调整大小等。拍摄者在客户端调整修改受损部位的位置区域后可以生成新的受损部位，然后将新的受损部位发送给服务器。In another embodiment, the photographer can interactively modify the position and size of the damaged portion. For example, the client determines the location area of the damaged part according to the sliding track of the photographer. If the photographer believes that the default generated location area does not completely cover the damaged part and needs to be adjusted, the position and size of the location area can be adjusted on the client. If the position area is selected by long-pressing the damaged part, move it, adjust the position of the damaged part, or stretch the frame of the damaged part position area to adjust the size. The photographer can generate a new damaged part after the client adjusts the location area of the damaged part, and then sends the new damaged part to the server.
这样，拍摄者可以方便、灵活根据实际现场受损部位情况调整受损部位在视频图像中的位置区域，更准确的定位受损部位，便于服务器更准确可靠的获取高质量的定损图像。In this way, the photographer can conveniently and flexibly adjust the position of the damaged part in the video image according to the actual damaged part of the scene, and more accurately locate the damaged part, so that the server can obtain a high-quality fixed-loss image more accurately and reliably.
确定出拍摄者指定的受损部位，将该受损部位的信息发送给服务器进行处理。The damaged part designated by the photographer is determined, and the information of the damaged part is sent to the server for processing.
S3：所述服务器接收所述客户端上传的拍摄视频数据和受损部位的信息，提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述受损部位的候选图像分类集合。S3: the server receives the captured video data and the damaged part information uploaded by the client, extracts a video image in the captured video data, and classifies the video image based on the information of the damaged part, and determines A candidate image classification set of the damaged portion.
车辆定损常常需要不同类别的图像数据，如整车的不同角度的图像、能展示出受损部件的图像、具体受损部位的近景细节图等。本申请在获取定损图像的处理中，可以对视频图像进行识别，如是否为受损车辆的图像、识别图像中 包含的车辆部件、包含一个还是多个车辆部件、车辆部件上是否有损伤等等。本申请实施例的一个场景中，可以将车辆定损需要的定损图像相应的分为不同的类别，其他不符合定损图像要求的可以单独另分为一个类别。具体的可以提取拍摄视频的每一帧图像，对每一帧图像进行识别后分类，形成受损部位的候选图像分类集合。Vehicle damage often requires different types of image data, such as images of different angles of the vehicle, images showing damaged parts, and close-up details of specific damaged parts. In the process of acquiring a fixed-loss image, the present application can identify a video image, such as whether it is an image of a damaged vehicle, a vehicle component included in the recognition image, whether one or more vehicle components are included, whether there is damage on the vehicle component, etc. Wait. In one scenario of the embodiment of the present application, the fixed loss images required for the vehicle to be damaged may be divided into different categories, and other requirements that do not meet the requirements of the fixed loss image may be separately classified into one category. Specifically, each frame of the captured video may be extracted, and each frame of the image is identified and classified to form a candidate image classification set of the damaged portion.
本申请提供所述方法的另一种实施例中，确定出的所述候选图像分类集合可以包括：In another embodiment of the method, the determined candidate image classification set may include:
S301：显示受损部位的近景图像集合、展示受损部位所属车辆部件的部件图像集合。S301: Display a close-up image set of the damaged part, and display a part image set of the vehicle component to which the damaged part belongs.
近景图像集合中包括了受损部位的近景图像，部件图像集合中包括了受损车辆的受损部件，受损部件上有至少一处受损部位。具体的在本实施例应用场景中，拍摄者可以对指定的受损部位进行由近到远(或者由远到近)的拍摄，可以通过拍摄者移动或者变焦来完成。服务器端可以对拍摄视频中的帧图像(可以是对每一帧图像进行处理，也可以选取一段视频的帧图像进行处理)进行分类和识别。在本实施例应用场景中，可以将拍摄视频的视频图像分成包括下述的3类，具体的包括：The close-up image collection includes a close-up image of the damaged portion, and the component image set includes the damaged component of the damaged vehicle, and the damaged component has at least one damaged portion. Specifically, in the application scenario of the embodiment, the photographer can perform shooting from near to far (or from far to near) on the specified damaged portion, which can be completed by the photographer moving or zooming. The server side can classify and identify the frame images in the captured video (which can be processed for each frame image or a frame image of a video segment). In the application scenario of the embodiment, the video image of the captured video may be divided into three categories, which are specifically included in the following:
a：近景图，为受损部位的近景图像，能清晰显示受损部位的细节信息；a: Close-up view, which is a close-up image of the damaged part, which can clearly display the details of the damaged part;
b：部件图，包含受损部位，并能展示受损部位所在的车辆部件；b: part drawing, containing the damaged part, and showing the vehicle parts where the damaged part is located;
c：a类和b类都不满足的图像。c: Images that are not satisfied by class a and class b.
具体的，可以根据定损图像中受损部位近景图像的需求来确定a类图像的识别算法/分类要求等。本申请在a类图像的识别处理过程中，一种实施方式中可以通过受损部位在当前所在的视频图像中所占区域的大小(面积或区域跨度)来识别确定。如果受损部位在视频图像中的占有较大区域(如大于一定阈值，比如长或者宽大于四分之一视频图像大小)，则可以确定该视频图像为a类图像。本申请提供的另一种实施方式中，如果在属于同一个受损部件的已分析处理帧图像中，当前受损部位相对于包含所述当前受损部位的其他已分析处理帧图像 的区域面积相对较大(处于一定比例或TOP范围内)，则可以确定该当前帧图像为a类图像。因此，本申请所述方法的另一种实施例中，可以采用下述中的至少一种方式确定所述近景图像集合中的视频图像：Specifically, the recognition algorithm/classification requirement of the class a image and the like may be determined according to the requirement of the near-field image of the damaged portion in the fixed-loss image. In the process of the identification process of the class A image, in one embodiment, the determination may be determined by the size (area or region span) of the area occupied by the damaged part in the currently located video image. If the damaged portion occupies a large area in the video image (eg, greater than a certain threshold, such as a length or a width greater than a quarter of the video image size), then the video image may be determined to be a type a image. In another embodiment provided by the present application, if the area of the analyzed portion of the analyzed frame image belonging to the same damaged component, the area of the current damaged portion relative to the image of the other analyzed processed frame containing the currently damaged portion Relatively large (within a certain ratio or TOP range), it can be determined that the current frame image is a type A image. Therefore, in another embodiment of the method of the present application, the video image in the close-up image set may be determined by at least one of the following methods:
S3011：受损部位在所属视频图像中所占区域的面积比值大于第一预设比例：S3011: The area ratio of the damaged area in the video image is greater than the first preset ratio:
S3012：受损部位的横坐标跨度与所属视频图像长度的比值大于第二预设比例，和/或，受损部位的纵坐标与所属视频图像高度的比例大于第三预设比例；S3012: the ratio of the abscissa span of the damaged part to the length of the associated video image is greater than the second preset ratio, and/or the ratio of the ordinate of the damaged part to the height of the associated video image is greater than the third preset ratio;
S3013：从相同受损部位的视频图像中，选择受损部位的面积降序后的前K张视频图像，或者所述面积降序后属于第四预设比例内的视频图像，K≥1。S3013: Select, from the video image of the same damaged part, the first K video images after the area of the damaged portion is descended, or the video image within the fourth preset ratio after the area is descended, K≥1.
a类型的受损细节图像中受损部位通常占据较大的区域范围，通过S3011中第一预设比例的设置，可以很好的控制受损部位细节图像的选取，得到符合处理需求的a类型图像。a类型图像中受损区域的面积可以通过所述受损区域所述包含的像素点统计得到。In the damaged detail image of type a, the damaged part usually occupies a large area range. By setting the first preset ratio in S3011, the selection of the detailed image of the damaged part can be well controlled, and the type of a that meets the processing requirements is obtained. image. The area of the damaged area in the a type image can be obtained by counting the pixel points contained in the damaged area.
另一个实施方式S3012中，也可以根据受损部位相对于视频图像的坐标跨度来确认是否为a类型图像。例如一个示例中，视频图像为800*650像素，受损车辆的损伤的两条较长的划痕，该划痕对应的横坐标跨度长600像素，每条划痕的跨度却很窄。虽然此时受损部位的区域面积不足所属视频图像的十分之一，但因该受损部位的横向跨度600像素占整个视频图像长度800像素的四分之三，则此时可以将该视频图像标记为a类型图像，如图4所示，图4是本申请一个实施例中基于指定的受损部位确定为近景图像的示意图。In another embodiment S3012, it is also possible to confirm whether or not it is an a-type image based on the coordinate span of the damaged portion with respect to the video image. For example, in one example, the video image is 800*650 pixels, two long scratches of the damaged vehicle damage, the scratch corresponding to the abscissa span is 600 pixels long, and the span of each scratch is narrow. Although the area of the damaged portion is less than one tenth of the video image of the video at this time, since the horizontal span of the damaged portion is 600 pixels, which is three quarters of the length of the entire video image, the video can be used at this time. The image is labeled as a type image, as shown in FIG. 4, which is a schematic diagram of determining a close-up image based on the designated damaged portion in one embodiment of the present application.
S3013中实施方式中，所述的受损部位的面积可以为S3011中的受损部位的区域面积，也可以为受损部位长或者高的跨度数值。In the embodiment of S3013, the area of the damaged portion may be the area of the damaged portion in S3011, or may be the span value of the damaged portion being long or high.
当然，也可以结合上述多种方式来识别出a类图像，如受损部位的区域面积既满足占用一定比例的视频图像，又在所有的相同受损区域图像中属于区域面积最大的第四预设比例范围内。本实施例场景中所述的a类图像通常包含受损部位的全部或者部分细节图像信息。Of course, a type of image can also be identified in combination with the above various methods, for example, the area of the damaged portion satisfies both a certain proportion of the video image and the fourth pre-region with the largest area in all the same damaged area images. Set within the proportional range. The class a image described in the scene of this embodiment typically contains all or part of the detailed image information of the damaged portion.
上述中所述的第一预设比例、第二预设比例、第三预设比例、第四预设比例等具体的可以根据图像识别精度或分类精度或其他处理需求等进行相应的设置，例如所述第二预设比例或第三预设比例取值可以为四分之一。The first preset ratio, the second preset ratio, the third preset ratio, and the fourth preset ratio described above may be specifically set according to image recognition accuracy or classification accuracy or other processing requirements, for example, The second preset ratio or the third preset ratio may be a quarter.
b类图像的识别处理的一种实现方式上，可以通过构建的车辆部件检测模型来识别视频图像中所包括的部件(如前保险杠、左前叶子板、右后门等)和其所在的位置。如果受损部位处于检测出的受损部件上，则可以确认该视频图像属于b类图像。In one implementation of the recognition processing of the b-type image, the components included in the video image (such as the front bumper, the left front fender, the right rear door, etc.) and the location thereof can be identified by the constructed vehicle component detection model. If the damaged portion is on the detected damaged component, it can be confirmed that the video image belongs to the b-type image.
本实施例中所述的部件检测模型使用深度神经网络检测出部件和部件在图像中的区域。本申请的一个实施例中可以基于卷积神经网络(Convolutional Neural Network，CNN)和区域建议网络(Region Proposal Network，RPN)，结合池化层、全连接层等构建所述部件损伤识别模型。例如部件识别模型中，可以使用基于卷积神经网络和区域建议网络的多种模型和变种，如Faster R-CNN、YOLO、Mask-FCN等。其中的卷积神经网络(CNN)可以用任意CNN模型，如ResNet、Inception,VGG等及其变种。通常神经网络中的卷积网络(CNN)部分可以使用在物体识别取得较好效果的成熟网络结构，如Inception、ResNet等网络，如ResNet网络，输入为一张图片，输出为多个部件区域，和对应的部件分类和置信度(这里的置信度为表示识别出来的车辆部件真实性程度的参量)。faster R-CNN、YOLO、Mask-FCN等都是属于本实施例可以使用的包含卷积层的深度神经网络。本实施例使用的深度神经网络结合区域建议层和CNN层能检测出所述待处理图像中的车辆部件，并确认所述车辆部件在待处理图像中的部件区域。具体的，本申请可以卷积网络(CNN)部分可以使用在物体识别取得很好效果的成熟网络结构，ResNet网络，该模型参数可以通过使用打标数据进行小批量梯度下降(mini-batch gradient descent)训练得到。The component detection model described in this embodiment uses a deep neural network to detect the regions of components and components in the image. In one embodiment of the present application, the component damage recognition model may be constructed based on a Convolutional Neural Network (CNN) and a Region Proposal Network (RPN) in combination with a pooling layer, a fully connected layer, and the like. For example, in the component recognition model, various models and variants based on convolutional neural networks and regional suggestion networks, such as Faster R-CNN, YOLO, Mask-FCN, etc., can be used. The convolutional neural network (CNN) can use any CNN model, such as ResNet, Inception, VGG, etc. and its variants. Generally, the convolutional network (CNN) part of the neural network can use a mature network structure that achieves better effects in object recognition, such as Inception, ResNet, etc., such as a ResNet network, where the input is a picture and the output is a plurality of component areas. And the corresponding component classification and confidence (the confidence here is a parameter indicating the degree of authenticity of the identified vehicle components). Fast R-CNN, YOLO, Mask-FCN, etc. are all deep neural networks including convolutional layers that can be used in this embodiment. The deep neural network used in this embodiment, in conjunction with the region suggestion layer and the CNN layer, can detect the vehicle components in the image to be processed and confirm the component regions of the vehicle component in the image to be processed. Specifically, the convolutional network (CNN) part of the present application can use a mature network structure in which object recognition achieves good effects, and a ResNet network, which can perform mini-batch gradient descent by using marking data. ) Training is available.
一种应用场景中，如果同一个视频图像同时满足a类和b类图像的判断逻辑，则可以同时属于a类和b类图像。In an application scenario, if the same video image satisfies the judgment logic of the class a and class b images at the same time, it can belong to the class a and class b images at the same time.
所述服务器可以提取所述拍摄视频数据中的视频图像，基于所述受损部位 在视频图像中的位置区域信息对所述视频图像进行分类，确定所述指定的受损部位的候选图像分类集合。The server may extract a video image in the captured video data, classify the video image based on location area information of the damaged part in the video image, and determine a candidate image classification set of the specified damaged part. .
S4：按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。S4: Select a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition.
可以根据定损图像的类别、清晰度等从所述候选图像分类集合中选取符合预设筛选条件的图像作为定损图像。所述的预设筛选条件可以自定义的设置，例如一种实施方式中，可以在a类和b类图像中根据图像的清晰度，分别选取多张(比如5或10张)清晰度最高，并且拍摄角度不一样的图像作为指定受损部位的定损图像。图像的清晰度可以通过对受损部位和检测出来的车辆部件所在的图像区域进行计算，例如可以使用基于空间域的算子(如Gabor算子)或者基于频域的算子(如快速傅立叶变换)等方法得到。对于a类图像中，通常需要保证一张或多个图像组合后可以显示受损部位中的全部区域，这样可以保障得到全面的受损区域信息。An image that meets the preset screening condition may be selected from the candidate image classification set according to the category, the sharpness, and the like of the fixed-loss image as the fixed-loss image. The preset screening condition may be a customized setting. For example, in one embodiment, multiple (eg, 5 or 10) sharpness may be selected according to the sharpness of the image in the type a and b images, respectively. And the image with different angles is taken as the fixed damage image of the designated damaged part. The sharpness of the image can be calculated by the image area where the damaged part and the detected vehicle part are located, for example, a space domain based operator (such as a Gabor operator) or a frequency domain based operator (such as a fast Fourier transform) can be used. ) and other methods are obtained. For a class A image, it is usually necessary to ensure that all or one of the damaged parts can be displayed after combining one or more images, thus ensuring comprehensive damage area information.
本申请提供的一种车辆定损图像获取方法，提供基于视频的车辆定损图像自动生成方案。拍摄者可以通过终端设备对受损车辆进行视频拍摄，并指定受损车辆的受损部位。拍摄的视频数据可以传输到系统的服务器端，系统在服务器端再对视频数据进行分析，获取定损所需的不同类别的候选图像，然后可以从候选图像中产生受损车辆的定损图像。利用本申请实施方案，可以自动、快速的生成符合定损处理需求的高质量定损图像，满足定损处理需求，提高定损图像的获取效率，同时也减少了保险公司作业人员的定损图像获取和处理成本。The invention provides a vehicle loss image acquisition method, which provides a video-based vehicle loss generation image automatic generation scheme. The photographer can video capture the damaged vehicle through the terminal device and specify the damaged part of the damaged vehicle. The captured video data can be transmitted to the server side of the system, and the system analyzes the video data on the server side to obtain different types of candidate images required for the loss, and then can generate a lossy image of the damaged vehicle from the candidate image. By using the embodiment of the present application, a high-quality fixed-loss image that meets the requirements of the fixed-loss processing can be automatically and quickly generated, meets the requirements of the fixed-loss processing, improves the acquisition efficiency of the fixed-loss image, and reduces the damage image of the insurance company operator. Get and process costs.
本申请所述方法的一个实施例中，所述客户端拍摄的视频传输给服务器，服务器可以根据受损部位实时跟踪受损部位在视频中的位置。如在上述实施例场景中，因为车辆为静止物体，移动终端在跟随拍摄者移动，此时可以采用一些图像算法求得拍摄视频相邻帧图像之间的对应关系，比如使用基于光流(optical flow)的算法，实现完成对受损部位的跟踪。如果移动终端存在比如加速 度仪和陀螺仪等传感器，则可以结合这些传感器的信号数据进一步确定拍摄者运动的方向和角度，实现更加精确的对受损部位的跟踪。因此，本申请所述方法的另一种实施例中，还可以包括：In an embodiment of the method described in the present application, the video captured by the client is transmitted to the server, and the server can track the location of the damaged part in the video in real time according to the damaged part. As in the above embodiment, since the mobile terminal is a stationary object and the mobile terminal is following the photographer, some image algorithms may be used to obtain a correspondence between the adjacent video images of the captured video, such as using optical flow (optical). Flow) algorithm to achieve tracking of damaged parts. If the mobile terminal has sensors such as an accelerometer and a gyroscope, the signal data of these sensors can be combined to further determine the direction and angle of the photographer's motion, thereby achieving more accurate tracking of the damaged portion. Therefore, in another embodiment of the method, the method may further include:
S200：服务器实时跟踪所述受损部位在所述拍摄视频数据中的位置区域；S200: The server tracks the location area of the damaged part in the captured video data in real time;
以及，在所述服务器判断所述受损部位脱离视频图像后重新进入视频图像时，基于所述受损部位的图像特征数据重新对所述受损部位的位置区域进行定位和跟踪。And, when the server determines that the damaged part re-enters the video image after leaving the video image, re-positioning and tracking the location area of the damaged part based on the image feature data of the damaged part.
服务器可以提取受损区域的图像特征数据，比如SIFT特征数据(Scale-invariant feature transform，尺度不变特征变换)。如果受损部位脱离视频图像后重新进入视频图像，系统能自动定位和继续跟踪，例如拍摄设备断电后重启或者拍摄区域位移到无损伤部位后又返回再次拍摄相同损伤部位。The server can extract image feature data of the damaged area, such as SIFT feature data (Scale-invariant feature transform). If the damaged part is detached from the video image and then re-entered the video image, the system can automatically locate and continue tracking. For example, if the shooting device is powered off and then restarted or the shooting area is displaced to the non-damaged part, it will return to shoot the same damaged part again.
拍摄者在客户端上指定车辆受损部位时，确定出的受损部位的位置区域可以实时显示在客户端上，以便于用户观察和确认受损部位。拍摄者通过客户端指定受损部位在图像中对应的位置区域，服务器可以自动跟踪指定受损部位，并且随着拍摄距离和角度变化，该受损部位在视频图像中对应的位置区域大小和位置也可以相应的变化。这样，服务器一侧可以实时展示客户端跟踪的受损部位，便于服务器的作业人员观察和使用。When the photographer specifies the damaged part of the vehicle on the client, the determined location area of the damaged part can be displayed on the client in real time, so that the user can observe and confirm the damaged part. The photographer specifies the damaged part in the corresponding position area of the image through the client, the server can automatically track the specified damaged part, and the size and position of the damaged part in the video image corresponding to the position and position of the damaged part. It can also be changed accordingly. In this way, the server side can display the damaged parts tracked by the client in real time, which is convenient for the server operator to observe and use.
另一种实施方式中，服务器在实时跟踪时可以将跟踪的所述受损部位的位置区域发送给客户端，这样客户端可以与服务器同步实时显示所述受损部位，以便于拍摄者观察服务器定位跟踪的受损部位。因此，所述方法的另一个实施例中，还可以包括：In another embodiment, the server can send the tracked location area of the damaged part to the client during real-time tracking, so that the client can display the damaged part in real time in synchronization with the server, so that the photographer can observe the server. Locate the damaged part of the track. Therefore, in another embodiment of the method, the method may further include:
S210：所述服务器将跟踪的所述受损部位的位置区域发送给所述客户端，以使客户端实时显示所述受损部位的位置区域。S210: The server sends the tracked location area of the damaged part to the client, so that the client displays the location area of the damaged part in real time.
另一种实施方式中，拍摄者可以交互式修改受损部位的位置和大小。例如客户端根据拍摄者的滑动轨迹确定受损部位的位置区域。若拍摄者认为默认生成的位置区域未能全部覆盖受损部位，需要调整，则可以再调整该位置区域的 位置和大小，如长按受损部位选择该位置区域后，进行移动，调整受损部位的位置，或者拉伸受损部位位置区域的边框可以调整大小等。拍摄者在客户端调整修改受损部位的位置区域后可以生成新的受损部位，然后将新的受损部位发送给服务器。同时，服务器可以同步更新客户端修改后的新的受损部位。服务器可以根据新的受损部位对后续的视频图像进行识别处理。具体的，本申请提供的所述方法的另一种实施例中，所述方法还可以包括：In another embodiment, the photographer can interactively modify the position and size of the damaged portion. For example, the client determines the location area of the damaged part according to the sliding track of the photographer. If the photographer believes that the default generated location area does not cover the damaged part and needs to be adjusted, the position and size of the position area can be adjusted. If the position is selected by long-pressing the damaged area, the movement is performed and the adjustment is damaged. The position of the part, or the frame of the area where the damaged part is stretched, can be resized or the like. The photographer can generate a new damaged part after the client adjusts the location area of the damaged part, and then sends the new damaged part to the server. At the same time, the server can synchronize the new damaged parts modified by the client. The server can identify subsequent video images based on the new damaged portion. Specifically, in another embodiment of the method provided by the application, the method may further include:
S220：接收所述客户端发送的新的受损部位，所述新的受损部位包括所述客户端基于接收的交互指令修改所述指定的受损部位的位置区域后重新确定的受损部位；S220: Receive a new damaged part sent by the client, where the new damaged part includes the damaged part that is re-determined after the client modifies the location area of the specified damaged part based on the received interactive instruction. ;
相应的，所述基于所述受损部位的信息对所述视频图像进行分类包括基于所述新的受损部位对视频图像进分类。Correspondingly, the classifying the video image based on the information of the damaged portion comprises classifying the video image based on the new damaged portion.
这样，拍摄者可以方便、灵活根据实际现场受损部位情况调整受损部位在视频图像中的位置区域，更准确的定位受损部位，便于服务器获取高质量的定损图像。In this way, the photographer can conveniently and flexibly adjust the position area of the damaged part in the video image according to the actual damaged part of the scene, and more accurately locate the damaged part, so that the server can obtain a high quality fixed loss image.
所述方法的另一个应用场景中，在拍摄受损部位的近景时，拍摄者可以对其从不同角度的连续拍摄。服务器一侧可以根据受损部位的跟踪，求得每帧图像的拍摄角度，进而选取一组不同角度的视频图像作为该受损部位的定损图像，从而确保定损图像能准确的反应出受损的类型和程度。因此，本申请所述方法的另一个实施例中，所述按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像包括：In another application scenario of the method, the photographer can continuously shoot from different angles when shooting a close-up of the damaged portion. The server side can obtain the shooting angle of each frame according to the tracking of the damaged part, and then select a set of video images of different angles as the fixed loss image of the damaged part, thereby ensuring that the fixed loss image can accurately reflect the received image. The type and extent of damage. Therefore, in another embodiment of the method of the present application, the determining, by the predetermined screening condition, the fixed loss image of the vehicle from the candidate image classification set comprises:
S401：从指定的所述受损部位候选图像分类集合中，根据视频图像的清晰度和所述受损部位的拍摄角度，分别选取至少一张视频图像作为所述受损部位的定损图像。S401: Select, from the specified damaged part candidate image classification set, at least one video image as the fixed loss image of the damaged part according to the definition of the video image and the shooting angle of the damaged part.
比如在一些事故现场中，部件变形在某些角度会相对于其他角度非常明显，或者如果受损部件有反光或者倒影，反光或者倒影会随着拍摄角度变化而变化 等，而利用本申请实施方案选取不同角度的图像作为定损图像，可以大幅减少这些因素对定损的干扰。可选的，如果客户端存在比如加速度仪和陀螺仪等传感器，也可以通过这些传感器的信号得到或者辅助计算得到拍摄角度。For example, in some accident scenes, the deformation of the component may be very obvious at some angles relative to other angles, or if the damaged component has reflection or reflection, the reflection or reflection may change with the change of the shooting angle, etc., and the embodiment of the present application is utilized. Selecting images of different angles as fixed loss images can greatly reduce the interference of these factors on the fixed loss. Optionally, if there are sensors such as accelerometers and gyroscopes on the client, the angles of the shots can also be obtained or assisted by the signals of these sensors.
具体的一个示例中，可以生成多个候选图像分类集合，但在具体选取定损图像时可以仅适用其中的一个或多个类型的候选图像分类集合，如上述所示的a类、b类和c类。选取最终需要的定损图像时，可以指定从a类和b类的候选图像分类集合中选取。在a类和b类图像中，可以根据视频图像的清晰度，分别选取多张(比如同一个部件的图像选取5张，同一个受损部位的图像选取10张)清晰度最高，并且拍摄角度不一样的图像作为定损图像。图像的清晰度可以通过对受损部位和检测出来的车辆部件部位所在的图像区域进行计算，例如可以使用基于空间域的算子(如Gabor算子)或者基于频域的算子(如快速傅立叶变换)等方法得到。一般的，对于a类图像，需要保证受损部位中的任意区域至少在一张图像中存在。In a specific example, multiple candidate image classification sets may be generated, but only one or more types of candidate image classification sets may be applied when specifically selecting the lossy image, such as the a class and the b class and the above. Class c. When selecting the final required fixed loss image, you can specify the candidate image classification set from class a and class b. In the type a and b images, multiple images can be selected according to the sharpness of the video image (for example, 5 images of the same component are selected, and 10 images of the same damaged portion are selected), and the sharpness is the highest, and the shooting angle is the same. Different images are used as the lossy image. The sharpness of the image can be calculated by calculating the image area of the damaged part and the detected part of the vehicle component, for example, a spatial domain based operator (such as Gabor operator) or a frequency domain based operator (such as fast Fourier) can be used. Transform) and other methods. In general, for a class A image, it is necessary to ensure that any area in the damaged portion exists in at least one image.
在本申请所述方法的一种应用场景中，拍摄者在移动终端视频拍摄时可以每次指定一个受损部位，然后传输至服务器进行处理，产生该受损部位的定损图像。另一种实施场景中，如果受损车辆存在多个受损部位，并且受损部位的距离很近，则用户可以同时指定多个受损部位。服务器可以同时跟踪这多个受损部位，并产生每个受损部位的定损图像。服务器对拍摄者指定的所有的受损部位都按照上述处理获取每个受损部位的定损图像，然后可以将所有产生的定损图像作为整个受损车辆的定损图像。图5是本申请所述方一种车辆定损图像获取方法的处理场景示意图，如图5所示，受损部位A和受损部位B距离较近，则可以同时进行跟踪处理，但受损部位C位于受损车辆的另一侧，在拍摄视频中距离受损部位A和受损部位B较远，则可以先不跟踪受损部位C，等受损部位A和受损部位B拍摄完后再单独拍摄受损部位C。因此本申请所述方法的另一个实施例中，若所接收到指定的至少两个受损部位，则可以判断所述至少两 个受损部位的距离是否符合设置的邻近条件；In an application scenario of the method described in the present application, the photographer can specify a damaged portion each time the video of the mobile terminal is captured, and then transmit it to the server for processing to generate a fixed-loss image of the damaged portion. In another implementation scenario, if there are multiple damaged parts in the damaged vehicle and the distance between the damaged parts is very close, the user can specify multiple damaged parts at the same time. The server can track the multiple damaged parts at the same time and generate a lossy image of each damaged part. The server acquires the damage image of each damaged part according to the above processing for all the damaged parts designated by the photographer, and then can use all the generated fixed loss images as the fixed damage image of the entire damaged vehicle. FIG. 5 is a schematic diagram of a processing scenario of a method for acquiring a fixed-loss image of a vehicle according to the present application. As shown in FIG. 5, when the damaged portion A and the damaged portion B are relatively close, the tracking processing may be performed at the same time, but the damage is performed. The part C is located on the other side of the damaged vehicle. If the distance between the damaged part A and the damaged part B is far away in the captured video, the damaged part C may not be tracked first, and the damaged part A and the damaged part B are photographed. Then take the damaged part C separately. Therefore, in another embodiment of the method of the present application, if the specified at least two damaged parts are received, it may be determined whether the distance of the at least two damaged parts meets the set neighboring condition;
若是，则同时跟踪所述至少两个受损部位，并分别产生相应的定损图像。If so, the at least two damaged parts are simultaneously tracked, and corresponding fixed loss images are respectively generated.
所述的邻近条件可以根据同一个视频图像中受损部位的个数、受损部位的大小、受损部位之间的距离等进行设置。The proximity condition may be set according to the number of damaged parts in the same video image, the size of the damaged part, the distance between the damaged parts, and the like.
如果服务器检测到所述受损部位的近景图像集合、部件图像集合中的至少一个为空，或者所述近景图像集合中的视频图像未覆盖到对应受损部位的全部区域时，则可以生成视频拍摄提示消息，然后可以向对应于所述拍摄视频数据的客户端发送所述视频拍摄提示消息。If the server detects that at least one of the close-up image set and the component image set of the damaged part is empty, or the video image in the close-up image set does not cover all areas corresponding to the damaged part, the video may be generated The prompt message is photographed, and then the video shooting prompt message may be sent to a client corresponding to the captured video data.
例如上述示例实施场景中，如果服务器无法得到能确定受损部位所在车辆部件的b类定损图像，则可以反馈给拍摄者，提示其拍摄包括受损部位在内的相邻多个车辆部件，从而确保得到(b)类定损图像。如果服务器无法得到a类定损图像，或者a类图像没能覆盖到受损部位的全部区域，则可以反馈给拍摄者，提示其拍摄受损部位的近景。For example, in the above example implementation scenario, if the server cannot obtain the b-type fixed-loss image that can determine the vehicle component in which the damaged portion is located, the camera can be fed back to the photographer to shoot adjacent vehicle components including the damaged portion. This ensures that the (b) type of lossy image is obtained. If the server cannot get a type a fixed loss image, or if the type a image does not cover the entire area of the damaged area, it can be fed back to the photographer to be prompted to take a close shot of the damaged part.
本申请所述方法的其他实施例中，如果服务器检测出拍摄的视频图像清晰度不足(低于一个事先设定的阈值或者低于最近一段拍摄视频中的平均清晰度)，则可以提示拍摄者缓慢移动，保证拍摄图像质量。例如反馈到移动终端APP上，提示用户拍摄图像时注意对焦，光照等影响清晰度的因素，如显示提示信息“速度过快，请缓慢移动，以保障图像质量”。In other embodiments of the method described herein, if the server detects that the captured video image is not sharp enough (below a predetermined threshold or lower than the average sharpness in the most recent captured video), the photographer may be prompted Move slowly to ensure the quality of the captured image. For example, feedback to the mobile terminal APP prompts the user to pay attention to the factors such as focus, illumination, etc. when shooting images, such as displaying the prompt message “The speed is too fast, please move slowly to ensure image quality”.
可选的，服务器可以保留产生定损图像的视频片段，以便于后续的查看和验证等。或者客户端可以在视频图像拍摄后将定损图像批量上传或者拷贝到远端服务器。Optionally, the server may retain the video segment that produces the lossy image for subsequent viewing and verification, and the like. Or the client can upload or copy the fixed loss image to the remote server after the video image is taken.
上述实施例所述车辆定损图像获取方法，提出了基于视频的车辆定损图像自动生成方案。拍摄者可以通过终端设备对受损车辆进行视频拍摄，并指定受损车辆的受损部位。拍摄的视频数据可以传输，获取定损所需的不同类别的候选图像。然后可以从候选图像中产生受损车辆的定损图像。利用本申请实施方案，可以自动、快速的生成符合定损处理需求的高质量定损图像，满足定损处 理需求，提高定损图像的获取效率，同时也减少了保险公司作业人员的定损图像获取和处理成本。In the vehicle loss detection image acquisition method described in the above embodiment, a video-based vehicle loss generation image automatic generation scheme is proposed. The photographer can video capture the damaged vehicle through the terminal device and specify the damaged part of the damaged vehicle. The captured video data can be transmitted to obtain different types of candidate images required for the loss. A fixed loss image of the damaged vehicle can then be generated from the candidate image. By using the embodiment of the present application, a high-quality fixed-loss image that meets the requirements of the fixed-loss processing can be automatically and quickly generated, meets the requirements of the fixed-loss processing, improves the acquisition efficiency of the fixed-loss image, and reduces the damage image of the insurance company operator. Get and process costs.
上述实施例从客户端与服务器交互的实施场景中描述了本申请通过受损车辆拍摄视频数据自动获取定损图像的实施方案。基于上述所述，本申请提供一种可以用于服务器一侧的车辆定损图像获取方法，图6是本申请所述方法另一个实施例的流程示意图，如图6所示，可以包括：The above embodiment describes an embodiment in which the present application automatically acquires a lossy image by capturing video data from a damaged vehicle from an implementation scenario in which the client interacts with the server. Based on the above, the present application provides a method for acquiring a vehicle's fixed-loss image on the server side. FIG. 6 is a schematic flowchart of another embodiment of the method of the present application. As shown in FIG. 6, the method may include:
S10：接收终端设备上传的受损车辆的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；S10: receiving shooting video data of the damaged vehicle and information of the damaged part uploaded by the terminal device, where the damaged part includes a damaged part designated to the damaged vehicle;
S11：提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述指定受损部位的候选图像分类集合；S11: extracting a video image in the captured video data, classifying the video image based on the information of the damaged part, and determining a candidate image classification set of the designated damaged part;
S12：按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。S12: Select a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition.
所述的终端设备可以为前述实施例所述的客户端，但本申请不排除可以为其他的终端设备，如数据库系统、第三方服务器、闪存等。在本实施例中，服务器接收客户端上传的或者拷贝来的对受损车辆进行拍摄获取的拍摄视频数据后，可以根据拍摄者对受损车辆指定的受损部位的信息对视频图像进行识别和分类。然后通过筛选自动生成车辆的定损图像。利用本申请实施方案，可以自动、快速的生成符合定损处理需求的高质量定损图像，满足定损处理需求，提高定损图像的获取效率，便于作业人员作业。The terminal device may be the client described in the foregoing embodiment, but the application does not exclude other terminal devices, such as a database system, a third-party server, a flash memory, and the like. In this embodiment, after receiving the captured video data acquired by the client for capturing and acquiring the damaged vehicle, the server may identify the video image according to the information of the damaged part specified by the photographer on the damaged vehicle. classification. The fixed loss image of the vehicle is then automatically generated by screening. With the embodiment of the present application, a high-quality fixed-loss image that meets the requirements of the fixed-loss processing can be automatically and quickly generated, meets the requirements of the fixed-loss processing, improves the acquisition efficiency of the fixed-loss image, and is convenient for the operator to work.
车辆定损常常需要不同类别的图像数据，如整车的不同角度的图像、能展示出受损部件的图像、具体受损部位的近景细节图等。本申请的一个实施例中，可以将需要的定损图像相应的分为不同的类别，具体的所述方法另一个实施例中，确定出的所述候选图像分类集合具体的可以包括：Vehicle damage often requires different types of image data, such as images of different angles of the vehicle, images showing damaged parts, and close-up details of specific damaged parts. In one embodiment of the present application, the required lossy image may be correspondingly divided into different categories. In another embodiment, the determined candidate image classification set may specifically include:
显示受损部位的近景图像集合、展示受损部位所属车辆部件的部件图像集合。A close-up image collection of the damaged portion is displayed, and a component image set of the vehicle component to which the damaged portion belongs is displayed.
一般的，所述部件图像集合中的视频图像中包括至少一处受损部位，如上 述所述的a类近景图、b类部件图、a类和b类都不满足的c类图像。Generally, the video image in the component image set includes at least one damaged portion, such as a class A close-up view, a b-type component map, a class b, and a b-type image that are not satisfied.
所述一种车辆定损图像获取方法的另一个实施例中，可以采用下述中的至少一种方式确定所述近景图像集合中的视频图像：In another embodiment of the method for acquiring a vehicle-damaged image, the video image in the close-up image set may be determined by at least one of the following:
受损部位在所属视频图像中所占区域的面积比值大于第一预设比例：The area ratio of the damaged portion in the area occupied by the video image is greater than the first preset ratio:
受损部位的横坐标跨度与所属视频图像长度的比值大于第二预设比例，和/或，受损部位的纵坐标与所属视频图像高度的比例大于第三预设比例；The ratio of the abscissa span of the damaged portion to the length of the video image to be associated is greater than the second preset ratio, and/or the ratio of the ordinate of the damaged portion to the height of the associated video image is greater than the third predetermined ratio;
从相同受损部位的视频图像中，选择受损部位的面积降序后的前K张视频图像，或者所述面积降序后属于第四预设比例内的视频图像，K≥1。From the video image of the same damaged part, the first K video images after the area of the damaged portion is descended, or the video image within the fourth preset ratio after the area descending is selected, K≥1.
具体的可以根据定损处理所需的受损部位近景图像的要求来确定a类图像的识别算法/分类要求等。本申请在a类图像的识别处理过程中，一种实施方式中可以通过受损部位在当前所在的视频图像中所占区域的大小(面积或区域跨度)来识别确定。如果受损部位在视频图像中的占有较大区域(如大于一定阈值，比如长或者宽大于四分之一视频图像大小)，则可以确定该视频图像为a类图像。本申请提供的另一种实施方式中，如果在对该受损部位所在的受损部件的其他已分析处理的当前帧图像中，该受损部位相对于其他相同受损部位的区域面积相对较大(处于一定比例或TOP范围内)，则可以确定该当前帧图像为a类图像。Specifically, the recognition algorithm/classification requirement of the class a image and the like can be determined according to the requirements of the near-field image of the damaged portion required for the fixed-loss processing. In the process of the identification process of the class A image, in one embodiment, the determination may be determined by the size (area or region span) of the area occupied by the damaged part in the currently located video image. If the damaged portion occupies a large area in the video image (eg, greater than a certain threshold, such as a length or a width greater than a quarter of the video image size), then the video image may be determined to be a type a image. In another embodiment provided by the present application, if the current frame image of the other analyzed processing of the damaged component where the damaged portion is located, the area of the damaged portion relative to the other damaged portion is relatively larger. Large (in a certain ratio or TOP range), it can be determined that the current frame image is a type A image.
所述一种车辆定损图像获取方法另一个实施例中，还可以包括：In another embodiment of the method for acquiring a vehicle-based image loss, the method further includes:
若检测到所述受损部位的近景图像集合、部件图像集合中的至少一个为空，或者所述近景图像集合中的视频图像未覆盖到对应受损部位的全部区域时，生成视频拍摄提示消息；Generating a video shooting prompt message if it is detected that at least one of the close-up image set and the component image set of the damaged portion is empty, or the video image in the close-up image set does not cover all areas corresponding to the damaged portion ;
向所述终端设备发送所述视频拍摄提示消息。Sending the video shooting prompt message to the terminal device.
所述的终端设备可以为前述与服务器交互的客户端，如手机。The terminal device may be a client that interacts with the server, such as a mobile phone.
所述一种车辆定损图像获取方法另一个实施例中，所述方法还可以包括：In another embodiment of the method for acquiring a vehicle-induced image loss, the method may further include:
实时跟踪所述受损部位在所述拍摄视频数据中的位置区域；Tracking a location area of the damaged portion in the captured video data in real time;
以及，在所述受损部位脱离视频图像后重新进入视频图像时，基于所述受损部位的图像特征数据重新对所述受损部位的位置区域进行定位和跟踪。And, when the damaged part is detached from the video image and then re-entered into the video image, the positional area of the damaged part is repositioned and tracked based on the image feature data of the damaged part.
重新定位和跟踪的受损部位的位置区域可以显示在服务器上。The location area of the damaged portion that is repositioned and tracked can be displayed on the server.
所述一种车辆定损图像获取方法另一个实施例中，所述方法还可以包括：In another embodiment of the method for acquiring a vehicle-induced image loss, the method may further include:
将跟踪的所述受损部位的位置区域发送至所述终端设备，以使所述终端设备实时显示所述受损部位的位置区域。And transmitting the tracked location area of the damaged part to the terminal device, so that the terminal device displays the location area of the damaged part in real time.
拍摄者在客户端上指定车辆受损部位时，确定出的受损部位的位置区域可以实时显示在客户端上，以便于用户观察和确认受损部位。拍摄者通过客户端指定受损部位在图像中对应的位置区域，服务器可以自动跟踪指定受损部位，将跟踪的所述受损部位的位置区域发送应于所述拍摄视频数据的终端设备。When the photographer specifies the damaged part of the vehicle on the client, the determined location area of the damaged part can be displayed on the client in real time, so that the user can observe and confirm the damaged part. The photographer specifies the damaged part in the corresponding position area in the image through the client, and the server can automatically track the designated damaged part, and transmit the tracked position area of the damaged part to the terminal device that captures the video data.
另一种实施方式中，拍摄者可以交互式修改受损部位的位置和大小。例如客户端根据拍摄者的滑动轨迹确定受损部位的位置区域。若拍摄者认为默认生成的位置区域未能全部覆盖受损部位，需要调整，则可以再调整该位置区域的位置和大小，如长按受损部位选择该位置区域后，进行移动，调整受损部位的位置，或者拉伸受损部位位置区域的边框可以调整大小等。拍摄者在客户端调整修改受损部位的位置区域后可以生成新的受损部位，然后将新的受损部位发送给服务器。同时，服务器可以同步更新客户端修改后的新的受损部位。服务器可以根据新的受损部位对后续的视频图像进行识别处理。因此，所述一种车辆定损图像获取方法另一个实施例中，所述方法还可以包括：In another embodiment, the photographer can interactively modify the position and size of the damaged portion. For example, the client determines the location area of the damaged part according to the sliding track of the photographer. If the photographer believes that the default generated location area does not cover the damaged part and needs to be adjusted, the position and size of the position area can be adjusted. If the position is selected by long-pressing the damaged area, the movement is performed and the adjustment is damaged. The position of the part, or the frame of the area where the damaged part is stretched, can be resized or the like. The photographer can generate a new damaged part after the client adjusts the location area of the damaged part, and then sends the new damaged part to the server. At the same time, the server can synchronize the new damaged parts modified by the client. The server can identify subsequent video images based on the new damaged portion. Therefore, in another embodiment of the method for acquiring a vehicle-damaged image, the method may further include:
接收所述终端设备发送的新的受损部位，所述新的受损部位包括所述终端设备基于接收的交互指令修改所述指定的受损部位的位置区域后重新确定的受损部位；Receiving a new damaged part sent by the terminal device, where the new damaged part includes the damaged part that is re-determined after the terminal device modifies the location area of the designated damaged part based on the received interactive instruction;
相应的，所述基于所述受损部位的信息对所述视频图像进行分类包括基于所述新的受损部位对视频图像进分类。Correspondingly, the classifying the video image based on the information of the damaged portion comprises classifying the video image based on the new damaged portion.
这样，拍摄者可以方便、灵活根据实际现场受损部位情况调整受损部位在 视频图像中的位置区域，更准确的定位受损部位，便于服务器获取高质量的定损图像。In this way, the photographer can conveniently and flexibly adjust the position of the damaged part in the video image according to the actual damaged part of the scene, and more accurately locate the damaged part, so that the server can obtain a high quality fixed loss image.
在拍摄受损部位的近景时，拍摄者可以对其从不同角度的连续拍摄。服务器一侧可以根据受损部位的跟踪，求得每帧图像的拍摄角度，进而选取一组不同角度的视频图像作为该受损部位的定损图像，从而确保定损图像能准确的反应出受损的类型和程度。因此，所述一种车辆定损图像获取方法另一个实施例中，所述按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像包括：When shooting close-up shots of damaged parts, the photographer can take continuous shots from different angles. The server side can obtain the shooting angle of each frame according to the tracking of the damaged part, and then select a set of video images of different angles as the fixed loss image of the damaged part, thereby ensuring that the fixed loss image can accurately reflect the received image. The type and extent of damage. Therefore, in another embodiment of the method for acquiring a vehicle-damaged image, the determining a fixed-loss image of the vehicle from the candidate image classification set according to a preset screening condition includes:
从指定的所述受损部位候选图像分类集合中，根据视频图像的清晰度和所述受损部位的拍摄角度，分别选取至少一张视频图像作为所述受损部位的定损图像。From the designated damaged part candidate image classification set, at least one video image is respectively selected as the fixed loss image of the damaged part according to the sharpness of the video image and the shooting angle of the damaged part.
如果受损车辆存在多个受损部位，并且受损部位的距离很近，则用户可以同时指定多个受损部位。服务器可以同时跟踪这多个受损部位，并产生每个受损部位的定损图像。服务器对拍摄者指定的所有的受损部位都按照上述处理获取每个受损部位的定损图像，然后可以将所有产生的定损图像作为整个受损车辆的定损图像。因此，所述一种车辆定损图像获取方法另一个实施例中，若接收到指定的至少两个受损部位，则判断所述至少两个受损部位的距离是否符合设置的邻近条件；If there are multiple damaged parts in the damaged vehicle and the distance between the damaged parts is very close, the user can specify multiple damaged parts at the same time. The server can track the multiple damaged parts at the same time and generate a lossy image of each damaged part. The server acquires the damage image of each damaged part according to the above processing for all the damaged parts designated by the photographer, and then can use all the generated fixed loss images as the fixed damage image of the entire damaged vehicle. Therefore, in another embodiment of the method for acquiring a fixed-size image of a vehicle, if at least two damaged parts are received, determining whether the distance of the at least two damaged parts meets the set neighboring condition;
若是，则同时跟踪所述至少两个受损部位，并分别产生相应的定损图像。If so, the at least two damaged parts are simultaneously tracked, and corresponding fixed loss images are respectively generated.
所述的邻近条件可以根据同一个视频图像中受损部位的个数、受损部位的大小、受损部位之间的距离等进行设置。The proximity condition may be set according to the number of damaged parts in the same video image, the size of the damaged part, the distance between the damaged parts, and the like.
基于前述客户端与服务器交互的实施场景中描述的通过受损车辆拍摄视频数据自动获取定损图像的实施方案，本申请还提供一种可以用于客户端一侧的车辆定损图像获取方法，图7是本申请所述方法另一个实施例的流程示意图， 如图7所示，可以包括：The present invention further provides an implementation method for acquiring a fixed-loss image of a vehicle that can be used on a client side, based on an embodiment of automatically acquiring a loss-of-loss image by capturing video data from a damaged vehicle, which is described in the foregoing implementation scenario of client-server interaction. FIG. 7 is a schematic flowchart of another embodiment of the method according to the present application. As shown in FIG. 7, the method may include:
S20：对受损车辆进行视频拍摄，获取拍摄视频数据；S20: performing video shooting on the damaged vehicle to obtain captured video data;
S21：接收对所述受损车辆指定的受损部位的信息；S21: receiving information about the damaged part specified by the damaged vehicle;
S22：将所述拍摄视频数据和所述受损部位的信息发送至处理终端；S22: Send the captured video data and the information of the damaged part to the processing terminal;
S23：接收所述处理终端返回的对所述受损部位实时跟踪的位置区域，在视频拍摄过程中实时显示所述跟踪的位置区域。S23: Receive a location area returned by the processing terminal and track the damaged part in real time, and display the tracked location area in real time during video shooting.
所述的处理终端包括对所述拍摄视频数据进行处理，基于指定受损部位的信息自动生成受损车辆的定损图像的终端设备，如可以为定损图像处理的远程服务器。The processing terminal includes a terminal device that processes the captured video data and automatically generates a lossy image of the damaged vehicle based on information specifying the damaged portion, such as a remote server that can be a fixed-loss image processing.
另一个实施例中，确定出的所述候选图像分类集合也可以包括：显示受损部位的近景图像集合、展示受损部位所属车辆部件的部件图像集合。如上述的a类图像、b类图像等。如果服务器无法得到能确定受损部位所在车辆部件的b类定损图像，服务器可以反馈给拍摄者发送视频拍摄提示消息，提示其拍摄包括受损部位在内的相邻多个车辆部件，从而确保得到b类定损图像。如果系统无法得到a类定损图像，或者a类图像没能覆盖到受损部位的全部区域，同样可以发送给拍摄者，提示其拍摄受损部位的近景图。因此，另一种实施例中，所述方法还可以包括：In another embodiment, the determined set of candidate image classifications may also include: displaying a close-up image set of the damaged portion, and displaying a component image set of the vehicle component to which the damaged portion belongs. Such as the above type a image, b type image, and the like. If the server is unable to obtain a type b fixed-loss image that identifies the vehicle component in which the damaged part is located, the server can feed back to the photographer to send a video capture alert message prompting him to take a number of adjacent vehicle components, including the damaged location, to ensure A type b fixed loss image is obtained. If the system cannot obtain a type A fixed loss image, or if the type a image does not cover the entire area of the damaged part, it can also be sent to the photographer to prompt him to take a close-up view of the damaged part. Therefore, in another embodiment, the method may further include:
S24：接收并显示所述处理终端发送的视频拍摄提示消息，所述视频拍摄提示消息包括在所述处理终端检测到所述受损部位的近景图像集合、部件图像集合中的至少一个为空，或者所述近景图像集合中的视频图像未覆盖到对应受损部位的全部区域时生成。S24: receiving and displaying a video shooting prompt message sent by the processing terminal, where the video shooting prompt message includes at least one of a close-up image set and a component image set of the damaged portion detected by the processing terminal being empty. Or generated when the video image in the close-up image set does not cover the entire area corresponding to the damaged part.
如前述所述，另一种实施方式中，客户端可以实时显示服务器跟踪的受损部位的位置区域，并且可以在客户端一侧交互式修改该位置区域的位置和大小。因此所述方法的另一个实施例中，还可以包括：As described above, in another embodiment, the client can display the location area of the damaged part tracked by the server in real time, and can interactively modify the position and size of the location area on the client side. Therefore, in another embodiment of the method, the method may further include:
S25：基于接收的交互指令修改所述受损部位的位置区域后，重新确定新的受损部位；S25: after modifying the location area of the damaged part based on the received interactive instruction, re-determining the new damaged part;
将所述新的受损部位发送给所述处理终端，以使所述处理终端基于所述新的受损部位对视频图像进行分类。Transmitting the new damaged portion to the processing terminal to cause the processing terminal to classify the video image based on the new damaged portion.
上述实施例提供的车辆定损图像获取方法，拍摄者可以通过终端设备对受损车辆进行视频拍摄，并指定受损车辆的受损部位。拍摄的视频数据可以传输到系统的服务器，服务器再对视频数据进行分析，获取定损所需的不同类别的候选图像，然后可以从候选图像中产生受损车辆的定损图像。利用本申请实施方案的终端设备，在终端设备上对受损部位进行视频拍摄并指定受损部位，这些数据信息发送给服务器，可以实现自动、快速的生成符合定损处理需求的高质量定损图像，满足定损处理需求，提高定损图像的获取效率，同时也减少了保险公司作业人员的定损图像获取和处理成本。In the vehicle loss imaging image acquisition method provided by the above embodiment, the photographer can perform video shooting on the damaged vehicle through the terminal device and specify the damaged portion of the damaged vehicle. The captured video data can be transmitted to the server of the system, and the server analyzes the video data to obtain different types of candidate images required for the loss, and then can generate a lossy image of the damaged vehicle from the candidate image. With the terminal device of the embodiment of the present application, video capture of the damaged part on the terminal device and designation of the damaged part, the data information is sent to the server, and the high-quality fixed loss that meets the requirement of the fixed loss processing can be automatically and quickly generated. The image satisfies the requirements of the fixed loss processing, improves the acquisition efficiency of the fixed loss image, and reduces the cost of obtaining and processing the fixed loss image of the insurance company operator.
前述实施例分别从客户端与服务器交互、客户端、服务器的角度的实施场景中描述了本申请通过受损车辆拍摄视频数据自动获取定损图像的实施方案。本申请的另一种实施方式中，拍摄者在客户端拍摄车辆视频时(或拍摄完成后)并指定车辆受损部位后，可以直接在客户端一侧对拍摄视频进行分析处理，并生成定损图像。具体的，图8是本申请所述方法另一个实施例的流程示意图，如图8所示，所述方法包括：The foregoing embodiment describes an implementation scheme for automatically acquiring a lossy image by capturing video data from a damaged vehicle from an implementation scenario of a client-server interaction, a client, and a server. In another implementation manner of the present application, when the photographer takes a video of the vehicle at the client (or after the shooting is completed) and specifies the damaged part of the vehicle, the captured video can be directly analyzed and processed on the client side, and generated. Damage image. Specifically, FIG. 8 is a schematic flowchart of another embodiment of the method according to the present application. As shown in FIG. 8, the method includes:
S30：接收对受损车辆的拍摄视频数据；S30: receiving shooting video data of the damaged vehicle;
S31：接收对所述受损车辆指定的受损部位的信息，基于所述受损部位的信息对所述拍摄视频数据中的视频图像进行识分类，确定所述受损部位的候选图像分类集合；S31: Receive information about the damaged part specified by the damaged vehicle, classify the video image in the captured video data based on the information of the damaged part, and determine a candidate image classification set of the damaged part. ;
S32：按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。S32: Select a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition.
具体的一个实现方式中可以由部署在客户端的应用模块组成。一般的，所述终端设备可以为具有视频拍摄功能和图像处理能力的通用或者专用设备，如手机、平板电脑等客户端。摄者使用可以客户端对受损车辆进行视频拍摄，同时对拍摄视频数据进行分析，产生定损图像。A specific implementation may be composed of application modules deployed on the client. Generally, the terminal device may be a general-purpose or special-purpose device with a video capturing function and an image processing capability, such as a mobile phone, a tablet computer, and the like. The photographer can use the client to video capture the damaged vehicle, and analyze the captured video data to generate a lossy image.
可选的，还可以包括一个服务器端，用来接收客户端生成的定损图像。客户端可以产生的定损图像实时或者异步传输至指定的服务器。因此，所述方法的另一个实施例中还可以包括：Optionally, a server side may also be included to receive the fixed loss image generated by the client. The fixed loss image that the client can generate is transmitted to the specified server in real time or asynchronously. Therefore, another embodiment of the method may further include:
S3201：将所述定损图像实时传输至指定的服务器；S3201: transmitting the fixed loss image to a specified server in real time;
或者，or,
S3202：将所述定损图像异步传输至指定的服务器。S3202: Asynchronously transfer the fixed loss image to a designated server.
图9是本申请所述方法另一个实施例的流程示意图，如图9所示，客户端可以将生成的定损图像立即上传给远端服务器，或者也可以在事后将定损图像批量上传或者拷贝到远端服务器。9 is a schematic flowchart of another embodiment of the method according to the present application. As shown in FIG. 9, the client may upload the generated loss image to the remote server immediately, or may upload the loss image in batches afterwards or Copy to the remote server.
基于前述服务器自动生成定损图像、受损部位定位跟踪等实施例的描述，本申请由客户端一侧自动生成定损图像的方法还可以包括其他的实施方式，如生成视频拍摄提示消息后直接显示在拍摄终端上、定损图像类别的具体划分和识别、分类方式，受损部位定位和跟踪等。具体的可以参照相关实施例的描述，在此不做一一赘述。The method for automatically generating a fixed-loss image by the client side may further include other implementation manners, such as directly generating a video shooting prompt message, based on the foregoing description of the embodiment of the server that automatically generates a fixed-loss image, a damaged portion location tracking, and the like. Displayed on the shooting terminal, specific division and recognition of the damage image category, classification, damage location and tracking. For details, refer to the description of the related embodiments, and details are not described herein.
本申请提供的一种车辆定损图像获取方法，在客户端一侧可以基于受损车辆的拍摄视频自动生成定损图像。拍摄者可以通过客户端对受损车辆进行视频拍摄，产生拍摄视频数据。然后再对拍摄视频数据进行分析，获取定损所需的不同类别的候选图像。进一步可以从候选图像中产生受损车辆的定损图像。利用本申请实施方案，可以直接在客户端一侧进行视频拍摄，并自动、快速的生成符合定损处理需求的高质量定损图像，满足定损处理需求，提高定损图像的获取效率，同时也减少了保险公司作业人员的定损图像获取和处理成本。The present invention provides a method for acquiring a vehicle damage image, which can automatically generate a loss image based on a captured video of a damaged vehicle on the client side. The photographer can video capture the damaged vehicle through the client to generate captured video data. Then, the captured video data is analyzed to obtain candidate images of different categories required for the fixed loss. Further, a lossy image of the damaged vehicle can be generated from the candidate image. With the implementation of the present application, video shooting can be directly performed on the client side, and a high-quality fixed-loss image that meets the requirements of the fixed-loss processing can be automatically and quickly generated to meet the requirements of the fixed-loss processing and improve the acquisition efficiency of the fixed-loss image. It also reduces the cost of acquiring and processing the damage image of insurance company operators.
基于上述所述的辆定损图像获取方法，本申请还提供一种车辆定损图像获取装置。所述的装置可以包括使用了本申请所述方法的系统(包括分布式系统)、软件(应用)、模块、组件、服务器、客户端等并结合必要的实施硬件的装置。基于同一创新构思，本申请提供的一种实施例中的装置如下面的实施例所述。 由于装置解决问题的实现方案与方法相似，因此本申请具体的装置的实施可以参见前述方法的实施，重复之处不再赘述。以下所使用的，术语“单元”或者“模块”可以实现预定功能的软件和/或硬件的组合。尽管以下实施例所描述的装置较佳地以软件来实现，但是硬件，或者软件和硬件的组合的实现也是可能并被构想的。具体的，图10是本申请提供的一种车辆定损图像获取装置实施例的模块结构示意图，如图10所示，所述装置可以包括：Based on the above-described fixed-loss image acquisition method, the present application further provides a vehicle-based damage image acquisition device. The apparatus may include a system (including a distributed system), software (applications), modules, components, servers, clients, etc., using the methods described herein in conjunction with the necessary means of implementing the hardware. Based on the same innovative concept, the apparatus in one embodiment provided by the present application is as described in the following embodiments. Since the implementation of the device to solve the problem is similar to the method, the implementation of the specific device of the present application can be referred to the implementation of the foregoing method, and the repeated description is not repeated. As used hereinafter, the term "unit" or "module" may implement a combination of software and/or hardware of a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware, or a combination of software and hardware, is also possible and contemplated. Specifically, FIG. 10 is a schematic structural diagram of a module of an embodiment of a vehicle-based image loss acquiring apparatus provided by the present application. As shown in FIG. 10, the apparatus may include:
数据接收模块101，可以用于接收终端设备上传的受损车辆的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；The data receiving module 101 may be configured to receive the captured video data of the damaged vehicle and the information of the damaged part uploaded by the terminal device, where the damaged part includes the damaged part designated for the damaged vehicle;
识别分类模块102，可以用于提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述指定受损部位的候选图像分类集合；The identification classification module 102 may be configured to extract a video image in the captured video data, classify the video image based on the information of the damaged portion, and determine a candidate image classification set of the designated damaged portion;
筛选模块103，可以用于按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。The screening module 103 is configured to select a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition.
上述所述的装置可以用于服务器一侧，实现对客户端上传的拍摄视频数据分析处理后获取定损图像。本申请还提供一种可以用于客户端一侧的车辆定损图像获取装置。如图11所示，图11为本申请所装置另一个实施例的模块结构示意图，具体的可以包括：The device described above can be used on the server side to obtain a fixed loss image after analyzing and processing the captured video data uploaded by the client. The present application also provides a vehicle damage image acquisition device that can be used on the client side. As shown in FIG. 11, FIG. 11 is a schematic structural diagram of a module according to another embodiment of the apparatus of the present application, and specifically includes:
拍摄模块201，可以用于对受损车辆进行视频拍摄，获取拍摄视频数据；The shooting module 201 can be configured to perform video shooting on the damaged vehicle to obtain captured video data.
交互模块201，可以用于接收对所述受损车辆指定的受损部位的信息；The interaction module 201 can be configured to receive information about the damaged part specified by the damaged vehicle;
通信模块202，可以用于将所述拍摄视频数据和所述受损部位的信息发送至处理终端；The communication module 202 is configured to send the captured video data and the information of the damaged part to the processing terminal;
跟踪模块203，可以用于接收所述处理终端返回的对所述受损部位实时跟踪的位置区域，以及显示所述跟踪的位置区域。The tracking module 203 is configured to receive a location area returned by the processing terminal and track the damaged part in real time, and display the tracked location area.
一种实施方式中，所述的交互模块201与跟踪模块203可以为同一个处理装置，如显示单元，拍摄者可以在显示单元中指定受损部位，同时也可以在显示单元中实施显示跟踪的受损部位的位置区域。In an implementation manner, the interaction module 201 and the tracking module 203 may be the same processing device, such as a display unit, and the photographer may specify the damaged portion in the display unit, and may also perform display tracking in the display unit. The location area of the damaged part.
本申请提供的车辆定损图像获取方法可以在计算机中由处理器执行相应的程序指令来实现。具体的，本申请提供的一种车辆定损图像获取装置的另一种实施例中，所述装置可以包括处理器以及用于存储处理器可执行指令的存储器，所述处理器执行所述指令时实现：The method for acquiring a vehicle damage image provided by the present application can be implemented by a processor executing a corresponding program instruction in a computer. Specifically, in another embodiment of the vehicle-based loss image acquiring apparatus provided by the present application, the apparatus may include a processor and a memory for storing processor-executable instructions, the processor executing the instruction Time to achieve:
接收受损车辆的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；Receiving captured video data of the damaged vehicle and information of the damaged portion, the damaged portion including the damaged portion designated for the damaged vehicle;
提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述指定受损部位的候选图像分类集合；Extracting a video image in the captured video data, classifying the video image based on information of the damaged portion, and determining a candidate image classification set of the designated damaged portion;
按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
所述的装置可以为服务器，服务器接收客户端上传的拍摄视频数据和受损部位的信息，然后进行分析处理，得到车辆的定损图像。另一种实施方式中，所述装置也可以为客户端，客户端对受损车辆进行视频拍摄后直接在客户端一侧进行分析处理，得到车辆的定损图像。因此，本申请所述装置的另一种实施例中，所述受损车辆的拍摄视频数据可以包括：The device may be a server, and the server receives the captured video data uploaded by the client and the information of the damaged part, and then performs analysis processing to obtain a fixed loss image of the vehicle. In another embodiment, the device may also be a client, and the client performs video processing on the damaged vehicle and directly analyzes and processes the image on the client side to obtain a fixed loss image of the vehicle. Therefore, in another embodiment of the apparatus of the present application, the captured video data of the damaged vehicle may include:
终端设备获取拍摄视频数据后上传的数据信息；The terminal device acquires data information uploaded after the video data is captured;
或者，or,
所述车辆定损图像获取装置对受损车辆进行视频拍摄获取的拍摄视频数据。The vehicle fixed-loss image acquiring device performs captured video data obtained by video capturing the damaged vehicle.
进一步的，在所述装置获取拍摄视频数据并直接进行分析处理获取定损图像的实施场景中，还可以将得到的定损图像发送给服务器，由服务器进行存储或进一步定损处理。因此，所述装置的另一种实施例中，若所述受损车辆的拍摄视频数据为所述车辆定损图像获取装置进行视频拍摄获取得到，则所述处理器执行所述指令时还包括：Further, in an implementation scenario in which the device acquires the captured video data and directly performs the analysis process to obtain the fixed-loss image, the obtained fixed-loss image may also be sent to the server for storage or further loss processing. Therefore, in another embodiment of the apparatus, if the captured video data of the damaged vehicle is obtained by video capture of the vehicle-damaged image acquisition device, the processor further includes when the instruction is executed. :
将所述定损图像实时传输至指定的处理终端；Transmitting the fixed loss image to a designated processing terminal in real time;
或者，or,
将所述定损图像异步传输至指定的处理终端。The fixed loss image is asynchronously transmitted to a designated processing terminal.
基于前述实施例方法或装置自动生成定损图像、受损部位定位跟踪等实施例的描述，本申请由客户端一侧自动生成定损图像的装置还可以包括其他的实施方式，如生成视频拍摄提示消息后直接显示在终端设备上、定损图像类别的具体划分和识别、分类方式，受损部位定位和跟踪等。具体的可以参照相关实施例的描述，在此不做一一赘述。The device or the device automatically generates a description of the embodiment of the fixed-loss image, the damaged portion location tracking, and the like. The device for automatically generating the fixed-loss image by the client side may further include other implementation manners, such as generating a video capture. After the prompt message, it is directly displayed on the terminal device, the specific division and identification of the fixed loss image category, the classification method, the location and tracking of the damaged part. For details, refer to the description of the related embodiments, and details are not described herein.
拍摄者可以通过本申请提供的车辆定损图像获取装置，对受损车辆进行视频拍摄，产生拍摄视频数据。然后再对拍摄视频数据进行分析，获取定损所需的不同类别的候选图像。进一步可以从候选图像中产生受损车辆的定损图像。利用本申请实施方案，可以直接在客户端一侧进行视频拍摄，并自动、快速的生成符合定损处理需求的高质量定损图像，满足定损处理需求，提高定损图像的获取效率，同时也减少了保险公司作业人员的定损图像获取和处理成本。The photographer can perform video shooting on the damaged vehicle through the vehicle damage image acquisition device provided by the present application to generate captured video data. Then, the captured video data is analyzed to obtain candidate images of different categories required for the fixed loss. Further, a lossy image of the damaged vehicle can be generated from the candidate image. With the implementation of the present application, video shooting can be directly performed on the client side, and a high-quality fixed-loss image that meets the requirements of the fixed-loss processing can be automatically and quickly generated to meet the requirements of the fixed-loss processing and improve the acquisition efficiency of the fixed-loss image. It also reduces the cost of acquiring and processing the damage image of insurance company operators.
本申请上述实施例所述的方法或装置可以通过计算机程序实现业务逻辑并记录在存储介质上，所述的存储介质可以计算机读取并执行，实现本申请实施例所描述方案的效果。因此，本申请还提供一种计算机可读存储介质，其上存储有计算机指令，所述指令被执行时可以实现以下步骤：The method or the device described in the above embodiments of the present application can implement the business logic and record on the storage medium by using a computer program, and the storage medium can be read and executed by the computer to achieve the effect of the solution described in the embodiment of the present application. Accordingly, the present application also provides a computer readable storage medium having stored thereon computer instructions that, when executed, may implement the following steps:
接收对受损车辆进行视频拍摄的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；Receiving captured video data for video capture of the damaged vehicle and information of the damaged portion, the damaged portion including the damaged portion designated for the damaged vehicle;
基于所述受损部位的信息对所述拍摄视频数据中的视频图像进行识分类，确定所述受损部位的候选图像分类集合；Determining a video image in the captured video data based on the information of the damaged portion, and determining a candidate image classification set of the damaged portion;
按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
本申请还提供的另一种计算机可读存储介质，其上存储有计算机指令，所述指令被执行时实现以下步骤：The present application further provides another computer readable storage medium having stored thereon computer instructions that, when executed, implement the following steps:
对受损车辆进行视频拍摄，获取拍摄视频数据；Video capture of damaged vehicles to obtain captured video data;
接收对所述受损车辆指定的受损部位的信息；Receiving information on the damaged portion designated for the damaged vehicle;
将所述拍摄视频数据和所述受损部位的信息发送至处理终端；Transmitting the captured video data and the information of the damaged part to a processing terminal;
接收所述处理终端返回的对所述受损部位实时跟踪的位置区域，在视频拍摄过程中实时显示所述跟踪的位置区域。Receiving a location area returned by the processing terminal and tracking the damaged part in real time, and displaying the tracked location area in real time during video shooting.
所述计算机可读存储介质可以包括用于存储信息的物理装置，通常是将信息数字化后再以利用电、磁或者光学等方式的媒体加以存储。本实施例所述的计算机可读存储介质有可以包括：利用电能方式存储信息的装置如，各式存储器，如RAM、ROM等；利用磁能方式存储信息的装置如，硬盘、软盘、磁带、磁芯存储器、磁泡存储器、U盘；利用光学方式存储信息的装置如，CD或DVD。当然，还有其他方式的可读存储介质，例如量子存储器、石墨烯存储器等等。The computer readable storage medium may include physical means for storing information, typically by digitizing the information and then storing it in a medium that utilizes electrical, magnetic or optical means. The computer readable storage medium of this embodiment may include: means for storing information by means of electrical energy, such as various types of memories, such as RAM, ROM, etc.; means for storing information by magnetic energy means, such as hard disk, floppy disk, magnetic tape, magnetic Core memory, bubble memory, U disk; means for optically storing information such as CD or DVD. Of course, there are other ways of readable storage media such as quantum memories, graphene memories, and the like.
上述所述的装置或方法或计算机可读存储介质可以用于获取车辆定损图像的服务器中，实现基于车辆图像视频自动获取车辆定损图像。所述的服务器可以是单独的服务器，也可以是多台应用服务器组成的系统集群，也可以是分布式系统中的服务器。具体的，一种实施例中，所述服务器可以包括处理器以及用于存储处理器可执行指令的存储器，所述处理器执行所述指令时实现：The apparatus or method described above or the computer readable storage medium may be used in a server for acquiring a vehicle loss image to automatically acquire a vehicle loss image based on the vehicle image video. The server may be a separate server, a system cluster composed of multiple application servers, or a server in a distributed system. Specifically, in an embodiment, the server may include a processor and a memory for storing processor-executable instructions, when the processor executes the instructions:
接收终端设备上传的受损车辆的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述指定受损部位的候选图像分类集合；按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。Receiving captured video data of the damaged vehicle and information of the damaged part uploaded by the terminal device, the damaged part including the damaged part designated for the damaged vehicle; extracting a video image in the captured video data, based on The information about the damaged portion classifies the video image, determines a candidate image classification set of the designated damaged portion, and selects a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition.
上述所述的装置或方法或计算机可读存储介质可以用于获取车辆定损图像的终端设备中，实现基于车辆图像视频自动获取车辆定损图像。所述的终端设备可以以服务器的方式实施，也可以为现场对受损车辆进行视频拍摄的客户端实施。图12是本申请提供的一种终端设备实施例的结构示意图，具体的，一种实施例中，所述终端上设备可以包括处理器以及用于存储处理器可执行指令的存储器，所述处理器执行所述指令时可以实现：The apparatus or method or the computer readable storage medium described above may be used in a terminal device for acquiring a vehicle loss image to automatically acquire a vehicle loss image based on a vehicle image video. The terminal device may be implemented in the form of a server, or may be implemented by a client that performs video shooting on the damaged vehicle in the field. 12 is a schematic structural diagram of an embodiment of a terminal device provided by the present application. Specifically, in an embodiment, the device on the terminal may include a processor and a memory for storing executable instructions of the processor, where the processing is performed. When the instruction is executed, it can be implemented:
获取对受损车辆进行视频拍摄的拍摄视频数据；Obtaining captured video data for video shooting of damaged vehicles;
接收对所述受损车辆指定的受损部位的信息；Receiving information on the damaged portion designated for the damaged vehicle;
基于所述受损部位的信息对所述拍摄视频数据中的视频图像进行识分类，确定所述受损部位的候选图像分类集合；Determining a video image in the captured video data based on the information of the damaged portion, and determining a candidate image classification set of the damaged portion;
按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
进一步的，如果所述终端设备为视频拍摄的客户端一侧的实施方式，则所述处理器执行所述指令时还可以实现：Further, if the terminal device is an implementation on the client side of the video capture, the processor may further implement the instruction:
将所述定损图像实时传输至指定的服务器；Transmitting the fixed loss image to a designated server in real time;
或者，or,
将所述定损图像异步传输至指定的服务器。The fixed loss image is transmitted asynchronously to the designated server.
拍摄者可以通过本申请提供的车辆定损图像的终端设备，对受损车辆进行视频拍摄，产生拍摄视频数据。然后再对拍摄视频数据进行分析，获取定损所需的不同类别的候选图像。进一步可以从候选图像中产生受损车辆的定损图像。利用本申请实施方案，可以直接在客户端一侧进行视频拍摄，并自动、快速的生成符合定损处理需求的高质量定损图像，满足定损处理需求，提高定损图像的获取效率，同时也减少了保险公司作业人员的定损图像获取和处理成本。The photographer can perform video shooting on the damaged vehicle through the terminal device of the vehicle-damaged image provided by the present application to generate captured video data. Then, the captured video data is analyzed to obtain candidate images of different categories required for the fixed loss. Further, a lossy image of the damaged vehicle can be generated from the candidate image. With the implementation of the present application, video shooting can be directly performed on the client side, and a high-quality fixed-loss image that meets the requirements of the fixed-loss processing can be automatically and quickly generated to meet the requirements of the fixed-loss processing and improve the acquisition efficiency of the fixed-loss image. It also reduces the cost of acquiring and processing the damage image of insurance company operators.
尽管本申请内容中提到受损区域跟踪方式、采用CNN和RPN网络检测车辆部件、基于受损部位的图像识别和分类等之类的数据模型构建、数据获取、交互、计算、判断等描述，但是，本申请并不局限于必须是符合行业通信标准、标准数据模型、计算机处理和存储规则或本申请实施例所描述的情况。某些行业标准或者使用自定义方式或实施例描述的实施基础上略加修改后的实施方案也可以实现上述实施例相同、等同或相近、或变形后可预料的实施效果。应用这些修改或变形后的数据获取、存储、判断、处理方式等获取的实施例，仍然可以属于本申请的可选实施方案范围之内。Although the content of this application refers to the description of damaged area tracking, detection of vehicle components using CNN and RPN networks, image recognition and classification based on damaged parts, data acquisition, interaction, calculation, judgment, etc., However, the application is not limited to situations that must be consistent with industry communication standards, standard data models, computer processing and storage rules, or embodiments of the present application. Certain industry standards or implementations that have been modified in a manner that uses a custom approach or an embodiment described above may also achieve the same, equivalent, or similar, or post-deformation implementation effects of the above-described embodiments. Embodiments obtained by applying these modified or modified data acquisition, storage, judgment, processing methods, etc., may still fall within the scope of alternative embodiments of the present application.
在20世纪90年代，对于一个技术的改进可以很明显地区分是硬件上的改进(例如，对二极管、晶体管、开关等电路结构的改进)还是软件上的改进(对 于方法流程的改进)。然而，随着技术的发展，当今的很多方法流程的改进已经可以视为硬件电路结构的直接改进。设计人员几乎都通过将改进的方法流程编程到硬件电路中来得到相应的硬件电路结构。因此，不能说一个方法流程的改进就不能用硬件实体模块来实现。例如，可编程逻辑器件(Programmable Logic Device,PLD)(例如现场可编程门阵列(Field Programmable Gate Array，FPGA))就是这样一种集成电路，其逻辑功能由用户对器件编程来确定。由设计人员自行编程来把一个数字系统“集成”在一片PLD上，而不需要请芯片制造厂商来设计和制作专用的集成电路芯片。而且，如今，取代手工地制作集成电路芯片，这种编程也多半改用“逻辑编译器(logic compiler)”软件来实现，它与程序开发撰写时所用的软件编译器相类似，而要编译之前的原始代码也得用特定的编程语言来撰写，此称之为硬件描述语言(Hardware Description Language，HDL)，而HDL也并非仅有一种，而是有许多种，如ABEL(Advanced Boolean Expression Language)、AHDL(Altera Hardware Description Language)、Confluence、CUPL(Cornell University Programming Language)、HDCal、JHDL(Java Hardware Description Language)、Lava、Lola、MyHDL、PALASM、RHDL(Ruby Hardware Description Language)等，目前最普遍使用的是VHDL(Very-High-Speed Integrated Circuit Hardware Description Language)与Verilog。本领域技术人员也应该清楚，只需要将方法流程用上述几种硬件描述语言稍作逻辑编程并编程到集成电路中，就可以很容易得到实现该逻辑方法流程的硬件电路。In the 1990s, improvements to a technology could clearly distinguish between hardware improvements (for example, improvements to circuit structures such as diodes, transistors, switches, etc.) or software improvements (for process flow improvements). However, as technology advances, many of today's method flow improvements can be seen as direct improvements in hardware circuit architecture. Designers almost always get the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be implemented by hardware entity modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is an integrated circuit whose logic function is determined by the user programming the device. Designers program themselves to "integrate" a digital system on a single PLD without having to ask the chip manufacturer to design and fabricate a dedicated integrated circuit chip. Moreover, today, instead of manually making integrated circuit chips, this programming is mostly implemented using "logic compiler" software, which is similar to the software compiler used in programming development, but before compiling The original code has to be written in a specific programming language. This is called the Hardware Description Language (HDL). HDL is not the only one, but there are many kinds, such as ABEL (Advanced Boolean Expression Language). AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc., are currently the most commonly used VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. It should also be apparent to those skilled in the art that the hardware flow for implementing the logic method flow can be easily obtained by simply programming the method flow into the integrated circuit with a few hardware description languages.
控制器可以按任何适当的方式实现，例如，控制器可以采取例如微处理器或处理器以及存储可由该(微)处理器执行的计算机可读程序代码(例如软件或固件)的计算机可读介质、逻辑门、开关、专用集成电路(Application Specific Integrated Circuit，ASIC)、可编程逻辑控制器和嵌入微控制器的形式，控制器的例子包括但不限于以下微控制器：ARC 625D、Atmel AT91SAM、Microchip PIC18F26K20以及Silicone Labs C8051F320，存储器控制器还可以被实现为存储器的控制逻辑的一部分。本领域技术人员也知道，除了以纯计算机可读程序 代码方式实现控制器以外，完全可以通过将方法步骤进行逻辑编程来使得控制器以逻辑门、开关、专用集成电路、可编程逻辑控制器和嵌入微控制器等的形式来实现相同功能。因此这种控制器可以被认为是一种硬件部件，而对其内包括的用于实现各种功能的装置也可以视为硬件部件内的结构。或者甚至，可以将用于实现各种功能的装置视为既可以是实现方法的软件模块又可以是硬件部件内的结构。The controller can be implemented in any suitable manner, for example, the controller can take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (eg, software or firmware) executable by the (micro)processor. In the form of logic gates, switches, application specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers, examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, The Microchip PIC18F26K20 and the Silicone Labs C8051F320, the memory controller can also be implemented as part of the memory's control logic. Those skilled in the art will also appreciate that in addition to implementing the controller in purely computer readable program code, the controller can be logically programmed by means of logic gates, switches, ASICs, programmable logic controllers, and embedding. The form of a microcontroller or the like to achieve the same function. Such a controller can therefore be considered a hardware component, and the means for implementing various functions included therein can also be considered as a structure within the hardware component. Or even a device for implementing various functions can be considered as a software module that can be both a method of implementation and a structure within a hardware component.
上述实施例阐明的系统、装置、模块或单元，具体可以由计算机芯片或实体实现，或者由具有某种功能的产品来实现。一种典型的实现设备为计算机。具体的，计算机例如可以为个人计算机、膝上型计算机、车载人机交互设备、蜂窝电话、相机电话、智能电话、个人数字助理、媒体播放器、导航设备、电子邮件设备、游戏控制台、平板计算机、可穿戴设备或者这些设备中的任何设备的组合。The system, device, module or unit illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product having a certain function. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a car-mounted human-machine interaction device, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet. A computer, wearable device, or a combination of any of these devices.
虽然本申请提供了如实施例或流程图所述的方法操作步骤，但基于常规或者无创造性的手段可以包括更多或者更少的操作步骤。实施例中列举的步骤顺序仅仅为众多步骤执行顺序中的一种方式，不代表唯一的执行顺序。在实际中的装置或终端产品执行时，可以按照实施例或者附图所示的方法顺序执行或者并行执行(例如并行处理器或者多线程处理的环境，甚至为分布式数据处理环境)。术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、产品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、产品或者设备所固有的要素。在没有更多限制的情况下，并不排除在包括所述要素的过程、方法、产品或者设备中还存在另外的相同或等同要素。Although the present application provides method operational steps as described in the embodiments or flowcharts, more or fewer operational steps may be included based on conventional or non-creative means. The order of the steps recited in the embodiments is only one of the many steps of the order of execution, and does not represent a single order of execution. When the actual device or terminal product is executed, it may be executed sequentially or in parallel according to the embodiment or the method shown in the drawings (for example, a parallel processor or a multi-threaded environment, or even a distributed data processing environment). The terms "comprising," "comprising," or "comprising" or "comprising" or "the" Elements, or elements that are inherent to such a process, method, product, or device. In the absence of further limitations, it is not excluded that there are additional identical or equivalent elements in the process, method, product, or device.
为了描述的方便，描述以上装置时以功能分为各种模块分别描述。当然，在实施本申请时可以把各模块的功能在同一个或多个软件和/或硬件中实现，也可以将实现同一功能的模块由多个子模块或子单元的组合实现等。以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能 划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。For the convenience of description, the above devices are described as being separately divided into various modules by function. Of course, in the implementation of the present application, the functions of each module may be implemented in the same software or software, or the modules that implement the same function may be implemented by a plurality of sub-modules or a combination of sub-units. The device embodiments described above are merely illustrative. For example, the division of the unit is only a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be combined or integrated. Go to another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.
本领域技术人员也知道，除了以纯计算机可读程序代码方式实现控制器以外，完全可以通过将方法步骤进行逻辑编程来使得控制器以逻辑门、开关、专用集成电路、可编程逻辑控制器和嵌入微控制器等的形式来实现相同功能。因此这种控制器可以被认为是一种硬件部件，而对其内部包括的用于实现各种功能的装置也可以视为硬件部件内的结构。或者甚至，可以将用于实现各种功能的装置视为既可以是实现方法的软件模块又可以是硬件部件内的结构。Those skilled in the art will also appreciate that in addition to implementing the controller in purely computer readable program code, the controller can be logically programmed by means of logic gates, switches, ASICs, programmable logic controllers, and embedding. The form of a microcontroller or the like to achieve the same function. Therefore, such a controller can be considered as a hardware component, and a device for internally implementing it for implementing various functions can also be regarded as a structure within a hardware component. Or even a device for implementing various functions can be considered as a software module that can be both a method of implementation and a structure within a hardware component.
本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (system), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or FIG. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine for the execution of instructions for execution by a processor of a computer or other programmable data processing device. Means for implementing the functions specified in one or more of the flow or in a block or blocks of the flow chart.
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。The computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device. The apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device. The instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.
在一个典型的配置中，计算设备包括一个或多个处理器(CPU)、输入/输出 接口、网络接口和内存。In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
内存可能包括计算机可读介质中的非永久性存储器，随机存取存储器(RAM)和/或非易失性内存等形式，如只读存储器(ROM)或闪存(flash RAM)。内存是计算机可读介质的示例。The memory may include non-persistent memory, random access memory (RAM), and/or non-volatile memory in a computer readable medium, such as read only memory (ROM) or flash memory. Memory is an example of a computer readable medium.
计算机可读介质包括永久性和非永久性、可移动和非可移动媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机的存储介质的例子包括，但不限于相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带，磁带磁磁盘存储或其他磁性存储设备或任何其他非传输介质，可用于存储可以被计算设备访问的信息。按照本文中的界定，计算机可读介质不包括暂存电脑可读媒体(transitory media)，如调制的数据信号和载波。Computer readable media includes both permanent and non-persistent, removable and non-removable media. Information storage can be implemented by any method or technology. The information can be computer readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory. (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disk read only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, Magnetic tape cartridges, magnetic tape storage or other magnetic storage devices or any other non-transportable media can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary storage of computer readable media, such as modulated data signals and carrier waves.
本领域技术人员应明白，本申请的实施例可提供为方法、系统或计算机程序产品。因此，本申请可采用完全硬件实施例、完全软件实施例或结合软件和硬件方面的实施例的形式。而且，本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。Those skilled in the art will appreciate that embodiments of the present application can be provided as a method, system, or computer program product. Thus, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment in combination of software and hardware. Moreover, the application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.
本申请可以在由计算机执行的计算机可执行指令的一般上下文中描述，例如程序模块。一般地，程序模块包括执行特定任务或实现特定抽象数据类型的例程、程序、对象、组件、数据结构等等。也可以在分布式计算环境中实践本申请，在这些分布式计算环境中，由通过通信网络而被连接的远程处理设备来执行任务。在分布式计算环境中，程序模块可以位于包括存储设备在内的本地和远程计算机存储介质中。The application can be described in the general context of computer-executable instructions executed by a computer, such as a program module. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform particular tasks or implement particular abstract data types. The present application can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are connected through a communication network. In a distributed computing environment, program modules can be located in both local and remote computer storage media including storage devices.
本说明书中的各个实施例均采用递进的方式描述，各个实施例之间相同相 似的部分互相参见即可，每个实施例重点说明的都是与其他实施例的不同之处。尤其，对于系统实施例而言，由于其基本相似于方法实施例，所以描述的比较简单，相关之处参见方法实施例的部分说明即可。在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本申请的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外，在不相互矛盾的情况下，本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。The various embodiments in the specification are described in a progressive manner, and similar parts of the various embodiments may be referred to each other, and each embodiment focuses on differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiment. In the description of the present specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means a specific feature described in connection with the embodiment or example. A structure, material or feature is included in at least one embodiment or example of the application. In the present specification, the schematic representation of the above terms is not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. In addition, various embodiments or examples described in the specification, as well as features of various embodiments or examples, may be combined and combined.
以上所述仅为本申请的实施例而已，并不用于限制本申请。对于本领域技术人员来说，本申请可以有各种更改和变化。凡在本申请的精神和原理之内所作的任何修改、等同替换、改进等，均应包含在本申请的权利要求范围之内。The above description is only an embodiment of the present application and is not intended to limit the application. Various changes and modifications can be made to the present application by those skilled in the art. Any modifications, equivalents, improvements, etc. made within the spirit and scope of the present application are intended to be included within the scope of the appended claims.

Claims (40)

  1. 一种车辆定损图像获取方法，所述方法包括：A method for acquiring a vehicle damage image, the method comprising:
    客户端获取拍摄视频数据，将所述拍摄视频数据发送至服务器；The client acquires the captured video data, and sends the captured video data to the server;
    所述客户端接收对受损车辆指定的受损部位的信息，将所述受损部位的信息发送至所述服务器；Receiving, by the client, information about the damaged part designated for the damaged vehicle, and transmitting the information of the damaged part to the server;
    所述服务器接收所述客户端上传的拍摄视频数据和受损部位的信息，提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述受损部位的候选图像分类集合；Receiving, by the server, the captured video data and the damaged part information uploaded by the client, extracting a video image in the captured video data, classifying the video image based on the information of the damaged part, and determining the a candidate image classification set of the damaged part;
    按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  2. 一种车辆定损图像获取方法，所述方法包括：A method for acquiring a vehicle damage image, the method comprising:
    接收终端设备上传的受损车辆的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；Receiving, by the terminal device, captured video data of the damaged vehicle and information of the damaged portion, the damaged portion including the damaged portion designated for the damaged vehicle;
    提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述指定受损部位的候选图像分类集合；Extracting a video image in the captured video data, classifying the video image based on information of the damaged portion, and determining a candidate image classification set of the designated damaged portion;
    按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  3. 如权利要求2所述的一种车辆定损图像获取方法，确定出的所述候选图像分类集合包括：The method for acquiring a fixed image of a vehicle according to claim 2, wherein the determined set of candidate image classifications comprises:
    显示受损部位的近景图像集合、展示受损部位所属车辆部件的部件图像集合。A close-up image collection of the damaged portion is displayed, and a component image set of the vehicle component to which the damaged portion belongs is displayed.
  4. 如权利要求3所述的一种车辆定损图像获取方法，采用下述中的至少一种方式确定所述近景图像集合中的视频图像：A method for acquiring a vehicle damage image according to claim 3, wherein the video image in the close-up image set is determined by at least one of the following:
    受损部位在所属视频图像中所占区域的面积比值大于第一预设比例：The area ratio of the damaged portion in the area occupied by the video image is greater than the first preset ratio:
    受损部位的横坐标跨度与所属视频图像长度的比值大于第二预设比例，和/或，受损部位的纵坐标与所属视频图像高度的比例大于第三预设比例；The ratio of the abscissa span of the damaged portion to the length of the video image to be associated is greater than the second preset ratio, and/or the ratio of the ordinate of the damaged portion to the height of the associated video image is greater than the third predetermined ratio;
    从相同受损部位的视频图像中，选择受损部位的面积降序后的前K张视频图像，或者所述面积降序后属于第四预设比例内的视频图像，K≥1。From the video image of the same damaged part, the first K video images after the area of the damaged portion is descended, or the video image within the fourth preset ratio after the area descending is selected, K≥1.
  5. 如权利要求3所述的一种车辆定损图像获取方法，还包括：A method for acquiring a vehicle damage image according to claim 3, further comprising:
    若检测到所述受损部位的近景图像集合、部件图像集合中的至少一个为空，或者所述近景图像集合中的视频图像未覆盖到对应受损部位的全部区域时，生成视频拍摄提示消息；Generating a video shooting prompt message if it is detected that at least one of the close-up image set and the component image set of the damaged portion is empty, or the video image in the close-up image set does not cover all areas corresponding to the damaged portion ;
    向所述终端设备发送所述视频拍摄提示消息。Sending the video shooting prompt message to the terminal device.
  6. 如权利要求2所述的一种车辆定损图像获取方法，所述方法还包括：A method for acquiring a vehicle damage image according to claim 2, the method further comprising:
    实时跟踪所述受损部位在所述拍摄视频数据中的位置区域；Tracking a location area of the damaged portion in the captured video data in real time;
    以及，在所述受损部位脱离视频图像后重新进入视频图像时，基于所述受损部位的图像特征数据重新对所述受损部位的位置区域进行定位和跟踪。And, when the damaged part is detached from the video image and then re-entered into the video image, the positional area of the damaged part is repositioned and tracked based on the image feature data of the damaged part.
  7. 如权利要求6所述的一种车辆定损图像获取方法，所述方法还包括：The method of acquiring a vehicle damage image according to claim 6, further comprising:
    将跟踪的所述受损部位的位置区域发送至所述终端设备，以使所述终端设备实时显示所述受损部位的位置区域。And transmitting the tracked location area of the damaged part to the terminal device, so that the terminal device displays the location area of the damaged part in real time.
  8. 如权利要求7所述的一种车辆定损图像获取方法，所述方法还包括：The method for acquiring a vehicle damage image according to claim 7, further comprising:
    接收所述终端设备发送的新的受损部位，所述新的受损部位包括所述终端设备基于接收的交互指令修改所述指定的受损部位的位置区域后重新确定的受损部位；Receiving a new damaged part sent by the terminal device, where the new damaged part includes the damaged part that is re-determined after the terminal device modifies the location area of the designated damaged part based on the received interactive instruction;
    相应的，所述基于所述受损部位的信息对所述视频图像进行分类包括基于所述新的受损部位对视频图像进分类。Correspondingly, the classifying the video image based on the information of the damaged portion comprises classifying the video image based on the new damaged portion.
  9. 如权利要求2至5中任意一项所述的一种车辆定损图像获取方法，所述按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像包括：The method for acquiring a fixed-size image of a vehicle according to any one of claims 2 to 5, wherein the selecting a fixed-loss image of the vehicle from the set of candidate image classifications according to a preset screening condition comprises:
    从指定的所述受损部位候选图像分类集合中，根据视频图像的清晰度和所述受损部位的拍摄角度，分别选取至少一张视频图像作为所述受损部位的定损图像。From the designated damaged part candidate image classification set, at least one video image is respectively selected as the fixed loss image of the damaged part according to the sharpness of the video image and the shooting angle of the damaged part.
  10. 如权利要求6至8中任意一项所述的一种车辆定损图像获取方法，若接收到指定的至少两个受损部位，则判断所述至少两个受损部位的距离是否符合设置的邻近条件；The method for acquiring a vehicle damage image according to any one of claims 6 to 8, if the specified at least two damaged parts are received, determining whether the distance of the at least two damaged parts conforms to the setting Neighboring condition
    若是，则同时跟踪所述至少两个受损部位，并分别产生相应的定损图像。If so, the at least two damaged parts are simultaneously tracked, and corresponding fixed loss images are respectively generated.
  11. 一种车辆定损图像获取方法，所述方法包括：A method for acquiring a vehicle damage image, the method comprising:
    对受损车辆进行视频拍摄，获取拍摄视频数据；Video capture of damaged vehicles to obtain captured video data;
    接收对所述受损车辆指定的受损部位的信息；Receiving information on the damaged portion designated for the damaged vehicle;
    将所述拍摄视频数据和所述受损部位的信息发送至处理终端；Transmitting the captured video data and the information of the damaged part to a processing terminal;
    接收所述处理终端返回的对所述受损部位实时跟踪的位置区域，显示所述跟踪的位置区域。Receiving a location area returned by the processing terminal and tracking the damaged part in real time, and displaying the tracked location area.
  12. 如权利要求11所述的一种车辆定损图像获取方法，还包括：The method for acquiring a vehicle damage image according to claim 11, further comprising:
    接收并显示所述处理终端发送的视频拍摄提示消息，所述视频拍摄提示消息包括在所述处理终端检测到所述受损部位的近景图像集合、部件图像集合中的至少一个为空，或者所述近景图像集合中的视频图像未覆盖到对应受损部位的全部区域时生成。Receiving and displaying a video shooting prompt message sent by the processing terminal, where the video shooting prompt message includes at least one of a close-up image set and a component image set of the damaged portion detected by the processing terminal being empty, or It is generated when the video image in the close-up image set does not cover the entire area corresponding to the damaged portion.
  13. 如权利要求11或12所述的一种车辆定损图像获取方法，所述方法还包括：The method for acquiring a vehicle damage image according to claim 11 or 12, further comprising:
    基于接收的交互指令修改所述受损部位的位置区域后，重新确定新的受损部位；Re-determining the new damaged part after modifying the location area of the damaged part based on the received interactive instruction;
    将所述新的受损部位发送给所述处理终端，以使所述处理终端基于所述新的受损部位对视频图像进行分类。Transmitting the new damaged portion to the processing terminal to cause the processing terminal to classify the video image based on the new damaged portion.
  14. 一种车辆定损图像获取方法，所述方法包括：A method for acquiring a vehicle damage image, the method comprising:
    接收受损车辆的拍摄视频数据；Receiving captured video data of the damaged vehicle;
    接收对所述受损车辆指定的受损部位的信息，基于所述受损部位的信息对所述拍摄视频数据中的视频图像进行识分类，确定所述受损部位的候选图像分类集合；Receiving information about the damaged part specified by the damaged vehicle, classifying the video image in the captured video data based on the information of the damaged part, and determining a candidate image classification set of the damaged part;
    按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  15. 如权利要求14所述的一种车辆定损图像获取方法，确定出的所述候选图像分类集合包括：The method for acquiring a vehicle image according to claim 14, wherein the determined set of candidate image classifications comprises:
    显示受损部位的近景图像集合、展示受损部位所属车辆部件的部件图像集合。A close-up image collection of the damaged portion is displayed, and a component image set of the vehicle component to which the damaged portion belongs is displayed.
  16. 如权利要求15所述的一种车辆定损图像获取方法，采用下述中的至少一种方式确定所述近景图像集合中的视频图像：A method for acquiring a vehicle damage image according to claim 15, wherein the video image in the close-up image set is determined by at least one of the following:
    受损部位在所属视频图像中所占区域的面积比值大于第一预设比例：The area ratio of the damaged portion in the area occupied by the video image is greater than the first preset ratio:
    受损部位的横坐标跨度与所属视频图像长度的比值大于第二预设比例，和/或，受损部位的纵坐标与所属视频图像高度的比例大于第三预设比例；The ratio of the abscissa span of the damaged portion to the length of the video image to be associated is greater than the second preset ratio, and/or the ratio of the ordinate of the damaged portion to the height of the associated video image is greater than the third predetermined ratio;
    从相同受损部位的视频图像中，选择受损部位的面积降序后的前K张视频图像，或者所述面积降序后属于第四预设比例内的视频图像，K≥1。From the video image of the same damaged part, the first K video images after the area of the damaged portion is descended, or the video image within the fourth preset ratio after the area descending is selected, K≥1.
  17. 如权利要求15所述的一种车辆定损图像获取方法，还包括：A method for acquiring a vehicle damage image according to claim 15, further comprising:
    若检测到所述受损部位的近景图像集合、部件图像集合中的至少一个为空，或者所述近景图像集合中的视频图像未覆盖到对应受损部位的全部区域时，生成视频拍摄提示消息；Generating a video shooting prompt message if it is detected that at least one of the close-up image set and the component image set of the damaged portion is empty, or the video image in the close-up image set does not cover all areas corresponding to the damaged portion ;
    显示所述视频拍摄提示消息。The video shooting prompt message is displayed.
  18. 如权利要求14所述的一种车辆定损图像获取方法，还包括：The method for acquiring a vehicle damage image according to claim 14, further comprising:
    实时跟踪并显示所述受损部位在所述拍摄视频数据中的位置区域；Tracking and displaying the location area of the damaged part in the captured video data in real time;
    以及，在所述受损部位脱离视频图像后重新进入视频图像时，基于所述受损部位的图像特征数据重新对所述受损部位的位置区域进行定位和跟踪。And, when the damaged part is detached from the video image and then re-entered into the video image, the positional area of the damaged part is repositioned and tracked based on the image feature data of the damaged part.
  19. 如权利要求18所述的一种车辆定损图像获取方法，还包括：A method for acquiring a vehicle damage image according to claim 18, further comprising:
    基于接收的交互指令修改所述受损部位的位置区域，重新确定新的受损部位；Modifying a location area of the damaged part based on the received interactive instruction to re-determine the new damaged part;
    相应的，所述基于所述受损部位的信息对所述视频图像进行分类包括基于所述新的受损部位对视频图像进分类。Correspondingly, the classifying the video image based on the information of the damaged portion comprises classifying the video image based on the new damaged portion.
  20. 如权利要求14至17中任意一项所述的一种车辆定损图像获取方法，所述按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像包括：The method for acquiring a vehicle damage image according to any one of claims 14 to 17, wherein the selecting a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition comprises:
    从指定的所述受损部位候选图像分类集合中，根据视频图像的清晰度和所 述受损部位的拍摄角度，分别选取至少一张视频图像作为所述受损部位的定损图像。From the designated set of candidate image classifications of the damaged parts, at least one video image is respectively selected as the fixed-loss image of the damaged portion according to the sharpness of the video image and the shooting angle of the damaged portion.
  21. 如权利要求18或19所述的一种车辆定损图像获取方法，若接收到指定的至少两个受损部位，则判断所述至少两个受损部位的距离是否符合设置的邻近条件；The method for acquiring a vehicle damage image according to claim 18 or 19, if the specified at least two damaged parts are received, determining whether the distance of the at least two damaged parts meets the set neighboring condition;
    若是，则同时跟踪所述至少两个受损部位，并分别产生相应的定损图像。If so, the at least two damaged parts are simultaneously tracked, and corresponding fixed loss images are respectively generated.
  22. 如权利要求14所述的一种车辆定损图像获取方法，还包括：The method for acquiring a vehicle damage image according to claim 14, further comprising:
    将所述定损图像实时传输至指定的服务器；Transmitting the fixed loss image to a designated server in real time;
    或者，or,
    将所述定损图像异步传输至指定的服务器。The fixed loss image is transmitted asynchronously to the designated server.
  23. 一种车辆定损图像获取装置，所述装置包括：A vehicle fixed-loss image acquiring device, the device comprising:
    数据接收模块，用于接收终端设备上传的受损车辆的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；a data receiving module, configured to receive captured video data of the damaged vehicle and information of the damaged part uploaded by the terminal device, where the damaged part includes a damaged part designated to the damaged vehicle;
    识别分类模块，用于提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述指定受损部位的候选图像分类集合；a classification module, configured to extract a video image in the captured video data, classify the video image based on the information of the damaged portion, and determine a candidate image classification set of the specified damaged portion;
    筛选模块，用于按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。And a screening module, configured to select a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition.
  24. 一种车辆定损图像获取装置，所述装置包括：A vehicle fixed-loss image acquiring device, the device comprising:
    拍摄模块，用于对受损车辆进行视频拍摄，获取拍摄视频数据；a shooting module for performing video shooting on a damaged vehicle to acquire captured video data;
    交互模块，用于接收对所述受损车辆指定的受损部位的信息；An interaction module, configured to receive information about the damaged part specified by the damaged vehicle;
    通信模块，用于将所述拍摄视频数据和所述受损部位的信息发送至处理终端；a communication module, configured to send the captured video data and the information of the damaged part to a processing terminal;
    跟踪模块，用于接收所述处理终端返回的对所述受损部位实时跟踪的位置区域，以及显示所述跟踪的位置区域。And a tracking module, configured to receive a location area returned by the processing terminal and track the damaged part in real time, and display the tracked location area.
  25. 一种车辆定损图像获取装置，包括处理器以及用于存储处理器可执行 指令的存储器，所述处理器执行所述指令时实现：A vehicle fixed loss image acquisition apparatus includes a processor and a memory for storing processor executable instructions, the processor implementing the instructions to:
    接收受损车辆的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；Receiving captured video data of the damaged vehicle and information of the damaged portion, the damaged portion including the damaged portion designated for the damaged vehicle;
    提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述指定受损部位的候选图像分类集合；Extracting a video image in the captured video data, classifying the video image based on information of the damaged portion, and determining a candidate image classification set of the designated damaged portion;
    按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  26. 如权利要求25所述的一种车辆定损图像获取装置，所述受损车辆的拍摄视频数据包括：A vehicle-defective image acquisition device according to claim 25, wherein the captured video data of the damaged vehicle comprises:
    终端设备获取拍摄视频数据后上传的数据信息；The terminal device acquires data information uploaded after the video data is captured;
    或者，or,
    所述车辆定损图像获取装置对受损车辆进行视频拍摄获取的拍摄视频数据。The vehicle fixed-loss image acquiring device performs captured video data obtained by video capturing the damaged vehicle.
  27. 如权利要求26所述的一种车辆定损图像获取装置，所述处理器执行所述指令时，确定出的所述候选图像分类集合包括：The vehicle-based image loss acquiring apparatus according to claim 26, wherein when the processor executes the instruction, the determined candidate image classification set comprises:
    显示受损部位的近景图像集合、展示受损部位所属车辆部件的部件图像集合。A close-up image collection of the damaged portion is displayed, and a component image set of the vehicle component to which the damaged portion belongs is displayed.
  28. 如权利要求27所述的一种车辆定损图像获取装置，所述处理器执行所述指令时，采用下述中的至少一种方式确定所述近景图像集合中的视频图像：A vehicle-defective image acquisition apparatus according to claim 27, wherein when said processor executes said instruction, said video image in said close-up image set is determined in at least one of:
    受损部位在所属视频图像中所占区域的面积比值大于第一预设比例：The area ratio of the damaged portion in the area occupied by the video image is greater than the first preset ratio:
    受损部位的横坐标跨度与所属视频图像长度的比值大于第二预设比例，和/或，受损部位的纵坐标与所属视频图像高度的比例大于第三预设比例；The ratio of the abscissa span of the damaged portion to the length of the video image to be associated is greater than the second preset ratio, and/or the ratio of the ordinate of the damaged portion to the height of the associated video image is greater than the third predetermined ratio;
    从相同受损部位的视频图像中，选择受损部位的面积降序后的前K张视频图像，或者所述面积降序后属于第四预设比例内的视频图像，K≥1。From the video image of the same damaged part, the first K video images after the area of the damaged portion is descended, or the video image within the fourth preset ratio after the area descending is selected, K≥1.
  29. 如权利要求28所述的一种车辆定损图像获取装置，所述处理器执行所述指令时还实现：A vehicle-defective image acquisition apparatus according to claim 28, wherein said processor executes said instruction further:
    若检测到所述受损部位的近景图像集合、部件图像集合中的至少一个为空， 或者所述近景图像集合中的视频图像未覆盖到对应受损部位的全部区域时，生成视频拍摄提示消息；Generating a video shooting prompt message if at least one of the close-up image set and the component image set of the damaged portion is detected to be empty, or the video image in the close-up image set does not cover all areas corresponding to the damaged portion ;
    所述视频拍摄提示消息用于显示在所述终端设备。The video shooting prompt message is displayed on the terminal device.
  30. 如权利要求26所述的一种车辆定损图像获取装置，所述处理器执行所述指令时还实现：A vehicle-defective image acquisition apparatus according to claim 26, wherein said processor executes said instruction further:
    实时跟踪所述受损部位在所述拍摄视频数据中的位置区域；Tracking a location area of the damaged portion in the captured video data in real time;
    以及，在所述受损部位脱离视频图像后重新进入视频图像时，基于所述受损部位的图像特征数据重新对所述受损部位的位置区域进行定位和跟踪。And, when the damaged part is detached from the video image and then re-entered into the video image, the positional area of the damaged part is repositioned and tracked based on the image feature data of the damaged part.
  31. 如权利要求30所述的一种车辆定损图像获取装置，若所拍摄视频数据为所述终端设备上传的数据信息，则所述处理器执行所述指令时还实现：The vehicle-based image loss acquiring apparatus according to claim 30, wherein if the captured video data is data information uploaded by the terminal device, the processor further executes:
    将跟踪的所述受损部位的位置区域发送至所述终端设备，以使所述终端设备实时显示所述受损部位的位置区域。And transmitting the tracked location area of the damaged part to the terminal device, so that the terminal device displays the location area of the damaged part in real time.
  32. 如权利要求26所述的一种车辆定损图像获取装置，所述处理器执行所述指令时还实现：A vehicle-defective image acquisition apparatus according to claim 26, wherein said processor executes said instruction further:
    接收修改所述受损部位的位置区域后重新确定新的受损部位；Re-determining the new damaged part after receiving the modification of the location area of the damaged part;
    相应的，所述基于所述受损部位的信息对所述视频图像进行分类包括基于所述新的受损部位对视频图像进分类。Correspondingly, the classifying the video image based on the information of the damaged portion comprises classifying the video image based on the new damaged portion.
  33. 如权利要求30所述的一种车辆定损图像获取装置，所述处理器执行所述指令时所述按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像包括：The vehicle-defective image acquisition device of claim 30, wherein the processor selecting the fixed-loss image of the vehicle from the candidate image classification set according to a preset screening condition when the processor executes the instruction comprises:
    从指定的所述受损部位候选图像分类集合中，根据视频图像的清晰度和所述受损部位的拍摄角度，分别选取至少一张视频图像作为所述受损部位的定损图像。From the designated damaged part candidate image classification set, at least one video image is respectively selected as the fixed loss image of the damaged part according to the sharpness of the video image and the shooting angle of the damaged part.
  34. 如权利要求30至32中任意一项所述的一种车辆定损图像获取装置，所述处理器执行所述指令时若接收到指定的至少两个受损部位，则判断所述至少两个受损部位的距离是否符合设置的邻近条件；The vehicle-defective image acquisition device according to any one of claims 30 to 32, wherein the processor determines the at least two if at least two damaged portions are received when the processor executes the instruction Whether the distance of the damaged part meets the set proximity condition;
    若是，则同时跟踪所述至少两个受损部位，并分别产生相应的定损图像。If so, the at least two damaged parts are simultaneously tracked, and corresponding fixed loss images are respectively generated.
  35. 如权利要求26所述的一种车辆定损图像获取装置，若所述受损车辆的拍摄视频数据为所述车辆定损图像获取装置进行视频拍摄获取得到，则所述处理器执行所述指令时还包括：A vehicle-defective image acquiring apparatus according to claim 26, wherein said processor executes said instruction if said captured video data of said damaged vehicle is obtained by video capturing of said vehicle-defective image acquiring means Also includes:
    将所述定损图像实时传输至指定的处理终端；Transmitting the fixed loss image to a designated processing terminal in real time;
    或者，or,
    将所述定损图像异步传输至指定的处理终端。The fixed loss image is asynchronously transmitted to a designated processing terminal.
  36. 一种计算机可读存储介质，其上存储有计算机指令，所述指令被执行时实现以下步骤：A computer readable storage medium having stored thereon computer instructions that, when executed, implement the following steps:
    接收对受损车辆进行视频拍摄的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；Receiving captured video data for video capture of the damaged vehicle and information of the damaged portion, the damaged portion including the damaged portion designated for the damaged vehicle;
    基于所述受损部位的信息对所述拍摄视频数据中的视频图像进行识分类，确定所述受损部位的候选图像分类集合；Determining a video image in the captured video data based on the information of the damaged portion, and determining a candidate image classification set of the damaged portion;
    按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  37. 一种计算机可读存储介质，其上存储有计算机指令，所述指令被执行时实现以下步骤：A computer readable storage medium having stored thereon computer instructions that, when executed, implement the following steps:
    对受损车辆进行视频拍摄，获取拍摄视频数据；Video capture of damaged vehicles to obtain captured video data;
    接收对所述受损车辆指定的受损部位的信息；Receiving information on the damaged portion designated for the damaged vehicle;
    将所述拍摄视频数据和所述受损部位的信息发送至处理终端；Transmitting the captured video data and the information of the damaged part to a processing terminal;
    接收所述处理终端返回的对所述受损部位实时跟踪的位置区域，在视频拍摄过程中实时显示所述跟踪的位置区域。Receiving a location area returned by the processing terminal and tracking the damaged part in real time, and displaying the tracked location area in real time during video shooting.
  38. 一种服务器，包括处理器以及用于存储处理器可执行指令的存储器，所述处理器执行所述指令时实现：A server comprising a processor and a memory for storing processor-executable instructions, the processor implementing the instructions to:
    接收终端设备上传的受损车辆的拍摄视频数据和受损部位的信息，所述受损部位包括对所述受损车辆指定的受损部位；提取所述拍摄视频数据中的视频图像，基于所述受损部位的信息对所述视频图像进行分类，确定所述指定受损 部位的候选图像分类集合；按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。Receiving captured video data of the damaged vehicle and information of the damaged part uploaded by the terminal device, the damaged part including the damaged part designated for the damaged vehicle; extracting a video image in the captured video data, based on The information about the damaged portion classifies the video image, determines a candidate image classification set of the designated damaged portion, and selects a fixed loss image of the vehicle from the candidate image classification set according to a preset screening condition.
  39. 一种终端设备，包括处理器以及用于存储处理器可执行指令的存储器，所述处理器执行所述指令时实现：A terminal device includes a processor and a memory for storing processor-executable instructions, the processor implementing the instructions to:
    获取对受损车辆进行视频拍摄的拍摄视频数据；Obtaining captured video data for video shooting of damaged vehicles;
    接收对所述受损车辆指定的受损部位的信息；Receiving information on the damaged portion designated for the damaged vehicle;
    基于所述受损部位的信息对所述拍摄视频数据中的视频图像进行识分类，确定所述受损部位的候选图像分类集合；Determining a video image in the captured video data based on the information of the damaged portion, and determining a candidate image classification set of the damaged portion;
    按照预设筛选条件从所述候选图像分类集合中选出车辆的定损图像。A fixed loss image of the vehicle is selected from the candidate image classification set according to a preset screening condition.
  40. 如权利要求39所述的一种终端设备，所述处理器执行所述指令时还实现：A terminal device according to claim 39, wherein said processor further implements said instruction:
    将所述定损图像实时传输至指定的服务器；Transmitting the fixed loss image to a designated server in real time;
    或者，or,
    将所述定损图像异步传输至指定的服务器。The fixed loss image is transmitted asynchronously to the designated server.
PCT/CN2018/084635 2017-04-28 2018-04-26 Method and apparatus for obtaining vehicle loss assessment image, server and terminal device WO2018196815A1 (en)

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